{"id":2269,"date":"2021-09-03T13:53:22","date_gmt":"2021-09-03T17:53:22","guid":{"rendered":"https:\/\/labs.icahn.mssm.edu\/minervalab\/?page_id=2269"},"modified":"2026-09-22T12:14:19","modified_gmt":"2026-09-22T16:14:19","slug":"scientific-computing-publications","status":"publish","type":"page","link":"https:\/\/labs.icahn.mssm.edu\/minervalab\/publications\/scientific-computing-publications\/","title":{"rendered":"Scientific Computing Publications"},"content":{"rendered":"<p>[et_pb_section bb_built=&#8221;1&#8243; fullwidth=&#8221;on&#8221; _builder_version=&#8221;4.9.0&#8243; _module_preset=&#8221;default&#8221; next_background_color=&#8221;#000000&#8243;][et_pb_fullwidth_menu admin_label=&#8221;Menu&#8221; menu_id=&#8221;15&#8243; menu_style=&#8221;centered&#8221; fullwidth_menu=&#8221;on&#8221; active_link_color=&#8221;#d80b8c&#8221; dropdown_menu_bg_color=&#8221;#221f72&#8243; dropdown_menu_line_color=&#8221;#221f72&#8243; dropdown_menu_active_link_color=&#8221;#d80b8c&#8221; _builder_version=&#8221;4.9.0&#8243; _module_preset=&#8221;default&#8221; menu_font=&#8221;|600|||||||&#8221; menu_text_color=&#8221;#FFFFFF&#8221; menu_font_size=&#8221;16px&#8221; background_color=&#8221;#221f72&#8243; background_layout=&#8221;dark&#8221; sticky_position=&#8221;top&#8221;]<\/p>\n<p><\/p>\n<p>[\/et_pb_fullwidth_menu][\/et_pb_section][et_pb_section bb_built=&#8221;1&#8243; _builder_version=&#8221;4.9.0&#8243; custom_padding=&#8221;0px||0px||false|false&#8221; prev_background_color=&#8221;#000000&#8243;][et_pb_row _builder_version=&#8221;4.9.0&#8243; _module_preset=&#8221;default&#8221; custom_padding=&#8221;||0px||false|false&#8221;][et_pb_column type=&#8221;4_4&#8243; _builder_version=&#8221;4.9.0&#8243; _module_preset=&#8221;default&#8221;][et_pb_text admin_label=&#8221;Breadcrumb&#8221; _builder_version=&#8221;4.9.0&#8243; _module_preset=&#8221;default&#8221;]<\/p>\n<p><a href=\"https:\/\/labs.icahn.mssm.edu\/minervalab\/scientific-computing-and-data\/\">Scientific Computing and Data<\/a>\u00a0\/\u00a0<a href=\"https:\/\/labs.icahn.mssm.edu\/minervalab\">High Performance Computing<\/a>\u00a0\/ <a href=\"https:\/\/labs.icahn.mssm.edu\/minervalab\/publications\/\">Publications<\/a> \/ Kovatch Publications<\/p>\n<p>[\/et_pb_text][\/et_pb_column][\/et_pb_row][et_pb_row _builder_version=&#8221;3.25&#8243; background_size=&#8221;initial&#8221; background_position=&#8221;top_left&#8221; background_repeat=&#8221;repeat&#8221;][et_pb_column type=&#8221;4_4&#8243; _builder_version=&#8221;3.25&#8243; custom_padding=&#8221;|||&#8221; custom_padding__hover=&#8221;|||&#8221;][et_pb_text admin_label=&#8221;Patricia Publications List&#8221; _builder_version=&#8221;4.27.4&#8243; header_font=&#8221;|700|||||||&#8221; header_text_color=&#8221;#221f72&#8243; background_size=&#8221;initial&#8221; background_position=&#8221;top_left&#8221; background_repeat=&#8221;repeat&#8221; background_pattern_color=&#8221;rgba(0,0,0,0.2)&#8221; background_mask_color=&#8221;#ffffff&#8221; text_text_shadow_horizontal_length=&#8221;text_text_shadow_style,%91object Object%93&#8243; text_text_shadow_horizontal_length_tablet=&#8221;0px&#8221; text_text_shadow_vertical_length=&#8221;text_text_shadow_style,%91object Object%93&#8243; text_text_shadow_vertical_length_tablet=&#8221;0px&#8221; text_text_shadow_blur_strength=&#8221;text_text_shadow_style,%91object Object%93&#8243; text_text_shadow_blur_strength_tablet=&#8221;1px&#8221; link_text_shadow_horizontal_length=&#8221;link_text_shadow_style,%91object Object%93&#8243; link_text_shadow_horizontal_length_tablet=&#8221;0px&#8221; link_text_shadow_vertical_length=&#8221;link_text_shadow_style,%91object Object%93&#8243; link_text_shadow_vertical_length_tablet=&#8221;0px&#8221; link_text_shadow_blur_strength=&#8221;link_text_shadow_style,%91object Object%93&#8243; link_text_shadow_blur_strength_tablet=&#8221;1px&#8221; ul_text_shadow_horizontal_length=&#8221;ul_text_shadow_style,%91object Object%93&#8243; ul_text_shadow_horizontal_length_tablet=&#8221;0px&#8221; ul_text_shadow_vertical_length=&#8221;ul_text_shadow_style,%91object Object%93&#8243; ul_text_shadow_vertical_length_tablet=&#8221;0px&#8221; ul_text_shadow_blur_strength=&#8221;ul_text_shadow_style,%91object Object%93&#8243; ul_text_shadow_blur_strength_tablet=&#8221;1px&#8221; ol_text_shadow_horizontal_length=&#8221;ol_text_shadow_style,%91object Object%93&#8243; 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header_text_shadow_vertical_length_tablet=&#8221;0px&#8221; header_text_shadow_blur_strength=&#8221;header_text_shadow_style,%91object Object%93&#8243; header_text_shadow_blur_strength_tablet=&#8221;1px&#8221; header_2_text_shadow_horizontal_length=&#8221;header_2_text_shadow_style,%91object Object%93&#8243; header_2_text_shadow_horizontal_length_tablet=&#8221;0px&#8221; header_2_text_shadow_vertical_length=&#8221;header_2_text_shadow_style,%91object Object%93&#8243; header_2_text_shadow_vertical_length_tablet=&#8221;0px&#8221; header_2_text_shadow_blur_strength=&#8221;header_2_text_shadow_style,%91object Object%93&#8243; header_2_text_shadow_blur_strength_tablet=&#8221;1px&#8221; header_3_text_shadow_horizontal_length=&#8221;header_3_text_shadow_style,%91object Object%93&#8243; header_3_text_shadow_horizontal_length_tablet=&#8221;0px&#8221; header_3_text_shadow_vertical_length=&#8221;header_3_text_shadow_style,%91object Object%93&#8243; header_3_text_shadow_vertical_length_tablet=&#8221;0px&#8221; header_3_text_shadow_blur_strength=&#8221;header_3_text_shadow_style,%91object Object%93&#8243; header_3_text_shadow_blur_strength_tablet=&#8221;1px&#8221; header_4_text_shadow_horizontal_length=&#8221;header_4_text_shadow_style,%91object Object%93&#8243; header_4_text_shadow_horizontal_length_tablet=&#8221;0px&#8221; header_4_text_shadow_vertical_length=&#8221;header_4_text_shadow_style,%91object Object%93&#8243; header_4_text_shadow_vertical_length_tablet=&#8221;0px&#8221; header_4_text_shadow_blur_strength=&#8221;header_4_text_shadow_style,%91object Object%93&#8243; header_4_text_shadow_blur_strength_tablet=&#8221;1px&#8221; header_5_text_shadow_horizontal_length=&#8221;header_5_text_shadow_style,%91object Object%93&#8243; header_5_text_shadow_horizontal_length_tablet=&#8221;0px&#8221; header_5_text_shadow_vertical_length=&#8221;header_5_text_shadow_style,%91object Object%93&#8243; header_5_text_shadow_vertical_length_tablet=&#8221;0px&#8221; header_5_text_shadow_blur_strength=&#8221;header_5_text_shadow_style,%91object Object%93&#8243; header_5_text_shadow_blur_strength_tablet=&#8221;1px&#8221; header_6_text_shadow_horizontal_length=&#8221;header_6_text_shadow_style,%91object Object%93&#8243; header_6_text_shadow_horizontal_length_tablet=&#8221;0px&#8221; header_6_text_shadow_vertical_length=&#8221;header_6_text_shadow_style,%91object Object%93&#8243; header_6_text_shadow_vertical_length_tablet=&#8221;0px&#8221; header_6_text_shadow_blur_strength=&#8221;header_6_text_shadow_style,%91object Object%93&#8243; header_6_text_shadow_blur_strength_tablet=&#8221;1px&#8221; box_shadow_horizontal_tablet=&#8221;0px&#8221; box_shadow_vertical_tablet=&#8221;0px&#8221; box_shadow_blur_tablet=&#8221;40px&#8221; box_shadow_spread_tablet=&#8221;0px&#8221; vertical_offset_tablet=&#8221;0&#8243; horizontal_offset_tablet=&#8221;0&#8243; z_index_tablet=&#8221;0&#8243;]<\/p>\n<h3>Publications Authored &amp; Co-Authored by Patricia Kovatch, Dean of Scientific Computing and Data<\/h3>\n<ul>\n<li data-section-id=\"1b1rqb1\" data-start=\"5621\" data-end=\"5808\"><span class=\"contents\" data-content-reference-start=\"6655\" data-content-reference-end=\"6785\"><span class=\"\" data-state=\"closed\"><a class=\"decorated-link\" href=\"https:\/\/www.researchgate.net\/scientific-contributions\/Patricia-Kovatch-2347859680?utm_source=chatgpt.com\" target=\"_blank\" rel=\"noopener\">Contrastive Transformer-Driven Discovery of Temporal Hemodynamic Subphenotypes in Cardiac Surgery Patients<\/a><\/span><\/span><strong data-start=\"5662\" data-end=\"5756\">. (Mar 2026) JM Desman, M Sabounchi, W Oh, G Kumar, \u2026 P Kovatch, \u2026 GN Nadkarni, A Sakhuja.<\/strong> <em data-start=\"5757\" data-end=\"5768\">Preprint.<\/em><\/li>\n<li data-section-id=\"n3zjmx\" data-start=\"5810\" data-end=\"6154\"><span class=\"contents\" data-content-reference-start=\"6916\" data-content-reference-end=\"7011\"><span class=\"\" data-state=\"closed\"><a class=\"decorated-link\" href=\"https:\/\/www.medrxiv.org\/content\/10.64898\/2026.05.17.26353406v1?utm_source=chatgpt.com\" target=\"_blank\" rel=\"noopener\">Evaluating Sycophancy in Frontier Models Using Persona-Driven Challenge<\/a><\/span><\/span><strong data-start=\"5851\" data-end=\"6045\">. (May 2026) NS Hazare, N Goel, C Yu, S Agaron, A Sharma, P Parchure, D Patel, P Timsina, B Kaplan, J Lampert, A Vakil, P Kovatch, B Darrow, BS Glicksberg, A Charney, GN Nadkarni, A Sakhuja.<\/strong> <em data-start=\"6046\" data-end=\"6114\">medRxiv preprint, May 20, 2026. DOI: 10.64898\/2026.05.17.26353406.<\/em><\/li>\n<li data-section-id=\"vt4ktc\" data-start=\"6156\" data-end=\"6655\"><span class=\"contents\" data-content-reference-start=\"7313\" data-content-reference-end=\"7457\"><span class=\"\" data-state=\"closed\"><a class=\"decorated-link\" href=\"https:\/\/www.medrxiv.org\/content\/10.64898\/2026.08.31.26361660v1.article-info?utm_source=chatgpt.com\" target=\"_blank\" rel=\"noopener\">Multidimensional Assurance of an Electronic Health Record Embedded Generative Artificial Intelligence Summarization Tool<\/a><\/span><\/span><strong data-start=\"6197\" data-end=\"6545\">. (Sept 2026) P Bodanki, C Capone, NS Hazare, S Agaron, M Vijayaraghavan, S Japa, I Zaretsky, J Epstein, AS Sawant, A Shaikh, E Leibner, A Sharma, S Gangadharan, T Ghani, HH Tai, D Ngai, S El-Haj, P Parchure, A Itwaru, B Kaplan, A Vakil, R Tamler, A Klein, R Freeman, P Kovatch, B Darrow, J McGreevy, L Stump, GN Nadkarni, P Timsina, A Sakhuja.<\/strong> <em data-start=\"6546\" data-end=\"6615\">medRxiv preprint, Sept. 7, 2026. DOI: 10.64898\/2026.08.31.26361660.<\/em><\/li>\n<li data-section-id=\"8twr2q\" data-start=\"4497\" data-end=\"4797\"><span class=\"contents\" data-content-reference-start=\"5233\" data-content-reference-end=\"5366\"><span class=\"\" data-state=\"closed\"><a class=\"decorated-link\" href=\"https:\/\/scholars.mssm.edu\/en\/publications\/automated-diagnosis-of-chronic-obstructive-pulmonary-disease-usin\/?utm_source=chatgpt.com\" target=\"_blank\" rel=\"noopener\">Automated diagnosis of chronic obstructive pulmonary disease using deep learning applied to electrocardiograms<\/a><\/span><\/span><strong data-start=\"4538\" data-end=\"4690\">. (Jan 2026) A Vaid, J Sharma, J Jiang, J Lampert, AS Sawant, E Argulian, S Lerakis, P Tandon, P Kovatch, C Powell, CB Cairns, GN Nadkarni, M Kraft.<\/strong><br data-start=\"4690\" data-end=\"4693\" \/><em data-start=\"4695\" data-end=\"4757\">eBioMedicine, 123, 106066. DOI: 10.1016\/j.ebiom.2025.106066.<\/em><\/li>\n<li data-section-id=\"121ynb7\" data-start=\"4799\" data-end=\"5103\"><span class=\"contents\" data-content-reference-start=\"5609\" data-content-reference-end=\"5789\"><span class=\"\" data-state=\"closed\"><a class=\"decorated-link\" href=\"https:\/\/scholars.mssm.edu\/en\/publications\/mapping-the-susceptibility-of-large-language-models-to-medical-mi\/?utm_source=chatgpt.com\" target=\"_blank\" rel=\"noopener\">Mapping the susceptibility of large language models to medical misinformation across clinical notes and social media: a cross-sectional benchmarking analysis<\/a><\/span><\/span><strong data-start=\"4840\" data-end=\"4981\">. (Jan 2026) M Omar, V Sorin, LH Wieler, AW Charney, P Kovatch, CR Horowitz, P Korfiatis, BS Glicksberg, R Freeman, GN Nadkarni, E Klang.<\/strong><br data-start=\"4981\" data-end=\"4984\" \/><em data-start=\"4986\" data-end=\"5063\">The Lancet Digital Health, 8(1), 100949. DOI: 10.1016\/j.landig.2025.100949.<\/em><\/li>\n<li data-section-id=\"ql64s6\" data-start=\"5105\" data-end=\"5419\"><span class=\"contents\" data-content-reference-start=\"6049\" data-content-reference-end=\"6198\"><span class=\"\" data-state=\"closed\"><a class=\"decorated-link\" href=\"https:\/\/pubmed.ncbi.nlm.nih.gov\/41352163\/?utm_source=chatgpt.com\" target=\"_blank\" rel=\"noopener\">The development of the Human Health Exposure Analysis Resource (HHEAR) Data Repository for environmental epidemiology research<\/a><\/span><\/span><strong data-start=\"5146\" data-end=\"5379\">. (Jan 2026 issue; published online Nov 29, 2025) JA Stingone, S Bengoa, C Valle, J Masters, T Cadenhead, A Rabin, P Pinheiro, M Bixby, M Mazzella, E Spear, H Santos, C Gennings, D McGuinness, P Kovatch, N Mervish, SL Teitelbaum.<\/strong><\/li>\n<li data-section-id=\"16o67vb\" data-start=\"730\" data-end=\"1114\"><span class=\"contents\" data-content-reference-start=\"775\" data-content-reference-end=\"864\"><span class=\"\" data-state=\"closed\"><a class=\"decorated-link\" href=\"https:\/\/scholars.mssm.edu\/en\/publications\/the-airms-data-platform-for-artificial-intelligence-in-healthcare\/?utm_source=chatgpt.com\" target=\"_blank\" rel=\"noopener\">The AIR\u00b7MS data platform for artificial intelligence in healthcare<\/a><\/span><\/span><strong data-start=\"769\" data-end=\"1011\">. (Dec 2025) P Guerrero, M Ernebjerg, T Holst, D Weese, H Dibello, S Ibing, L Schmidt, R Ungaro, B Renard, C Lippert, E Alleva, TD Quinn, P Kovatch, EM Antao, E Heyneke, A Rasheed, S Kalabakov, B Arnrich, A Charney, LH Wieler, G Nadkarni.<\/strong><br data-start=\"1011\" data-end=\"1014\" \/><em data-start=\"1016\" data-end=\"1076\">JAMIA Open, 8(6), ooaf145. DOI: 10.1093\/jamiaopen\/ooaf145.<\/em><\/li>\n<li data-section-id=\"1myumn6\" data-start=\"1116\" data-end=\"1527\"><span class=\"contents\" data-content-reference-start=\"1209\" data-content-reference-end=\"1345\"><span class=\"\" data-state=\"closed\"><a class=\"decorated-link\" href=\"https:\/\/scholars.mssm.edu\/en\/publications\/personalized-fluid-management-in-patients-with-sepsis-and-acute-k\/?utm_source=chatgpt.com\" target=\"_blank\" rel=\"noopener\">Personalized Fluid Management in Patients with Sepsis and Acute Kidney Injury: A Causal Machine Learning Approach<\/a><\/span><\/span><strong data-start=\"1155\" data-end=\"1406\">. (Dec 2025) W Oh, K Takkavatakarn, Z Al-Taie, H Kittrell, K Shawwa, H Gomez, AS Sawant, P Tandon, G Kumar, M Sterling, I Hofer, L Chan, J Oropello, R Kohli-Seth, AW Charney, M Kraft, P Kovatch, M Su\u00e1rez-Fari\u00f1as, JA Kellum, GN Nadkarni, A Sakhuja.<\/strong><br data-start=\"1406\" data-end=\"1409\" \/><em data-start=\"1411\" data-end=\"1489\">Critical Care Explorations, 7(12), e1354. DOI: 10.1097\/CCE.0000000000001354.<\/em><\/li>\n<li data-section-id=\"lj9tuw\" data-start=\"1529\" data-end=\"2009\"><span class=\"contents\" data-content-reference-start=\"1704\" data-content-reference-end=\"1798\"><span class=\"\" data-state=\"closed\"><a class=\"decorated-link\" href=\"https:\/\/scholars.mssm.edu\/en\/publications\/identifying-bias-at-scale-in-clinical-notes-using-large-language-\/?utm_source=chatgpt.com\" target=\"_blank\" rel=\"noopener\">Identifying Bias at Scale in Clinical Notes Using Large Language Models<\/a><\/span><\/span><strong data-start=\"1568\" data-end=\"1875\">. (Dec 2025) DU Apakama, KAN Nguyen, D Hyppolite, S Soffer, A Mudrik, E Ling, A Moses, I Temnycky, A Glasser, R Anderson, P Parchure, E Woullard, M Edalati, L Chan, C Kronk, R Freeman, A Kia, P Timsina, MA Levin, R Khera, P Kovatch, AW Charney, BG Carr, LD Richardson, CR Horowitz, E Klang, GN Nadkarni.<\/strong><br data-start=\"1875\" data-end=\"1878\" \/><em data-start=\"1880\" data-end=\"1971\">Mayo Clinic Proceedings: Digital Health, 3(4), 100296. DOI: 10.1016\/j.mcpdig.2025.100296.<\/em><\/li>\n<li data-section-id=\"s1mws\" data-start=\"2011\" data-end=\"2298\"><span class=\"contents\" data-content-reference-start=\"2225\" data-content-reference-end=\"2346\"><span class=\"\" data-state=\"closed\"><a class=\"decorated-link\" href=\"https:\/\/scholars.mssm.edu\/en\/publications\/infehr-clinical-phenotype-resolution-through-deep-geometric-learn\/?utm_source=chatgpt.com\" target=\"_blank\" rel=\"noopener\">InfEHR: Clinical phenotype resolution through deep geometric learning on electronic health records<\/a><\/span><\/span><strong data-start=\"2050\" data-end=\"2188\">. (Dec 2025) J Kauffman, E Holmes, A Vaid, AW Charney, P Kovatch, J Lampert, A Sakhuja, M Zitnik, BS Glicksberg, I Hofer, GN Nadkarni.<\/strong><br data-start=\"2188\" data-end=\"2191\" \/><em data-start=\"2193\" data-end=\"2260\">Nature Communications, 16, 8475. DOI: 10.1038\/s41467-025-63366-6.<\/em><\/li>\n<li><span class=\"contents\" data-content-reference-start=\"2612\" data-content-reference-end=\"2761\"><span class=\"\" data-state=\"closed\"><a class=\"decorated-link\" href=\"https:\/\/pubmed.ncbi.nlm.nih.gov\/41352163\/?utm_source=chatgpt.com\" target=\"_blank\" rel=\"noopener\">The development of the Human Health Exposure Analysis Resource (HHEAR) Data Repository for environmental epidemiology research<\/a><\/span><\/span><strong data-start=\"2360\" data-end=\"2573\">. (Nov 2025 \/ Jan 2026 issue) JA Stingone, S Bengoa, C Valle, J Masters, T Cadenhead, A Rabin, P Pinheiro, M Bixby, M Mazzella, E Spear, H Santos, C Gennings, D McGuinness, P Kovatch, N Mervish, SL Teitelbaum.<\/strong><br data-start=\"2573\" data-end=\"2576\" \/><em data-start=\"2578\" data-end=\"2654\">Environment International, 207, 109967. DOI: 10.1016\/j.envint.2025.109967.<\/em><\/li>\n<li><span class=\"contents\" data-content-reference-start=\"3112\" data-content-reference-end=\"3217\"><span class=\"\" data-state=\"closed\"><a class=\"decorated-link\" href=\"https:\/\/scholars.mssm.edu\/en\/publications\/a-scalable-framework-for-benchmark-embedding-models-in-semantic-h\/?utm_source=chatgpt.com\" target=\"_blank\" rel=\"noopener\">A scalable framework for benchmark embedding models in semantic health-care tasks<\/a><\/span><\/span><strong data-start=\"2757\" data-end=\"2883\">. (Sept 2025) S Soffer, M Omar, M Gendler, BS Glicksberg, P Kovatch, O Efros, R Freeman, AW Charney, GN Nadkarni, E Klang.<\/strong><br data-start=\"2883\" data-end=\"2886\" \/><em data-start=\"2888\" data-end=\"2946\">Journal of the American Medical Informatics Association.<\/em><\/li>\n<li><span class=\"contents\" data-content-reference-start=\"3429\" data-content-reference-end=\"3550\"><span class=\"\" data-state=\"closed\"><a class=\"decorated-link\" href=\"https:\/\/www.nature.com\/articles\/s41467-025-63366-6?utm_source=chatgpt.com\" target=\"_blank\" rel=\"noopener\">InfEHR: Clinical phenotype resolution through deep geometric learning on electronic health records<\/a><\/span><\/span><strong data-start=\"3029\" data-end=\"3168\">. (Sept 2025) J Kauffman, E Holmes, A Vaid, AW Charney, P Kovatch, J Lampert, A Sakhuja, M Zitnik, BS Glicksberg, I Hofer, GN Nadkarni.<\/strong><br data-start=\"3168\" data-end=\"3171\" \/><em data-start=\"3173\" data-end=\"3266\">Nature Communications, 16, 8475. Published Sept. 26, 2025. DOI: 10.1038\/s41467-025-63366-6.<\/em><\/li>\n<li><span class=\"contents\" data-content-reference-start=\"3828\" data-content-reference-end=\"3965\"><span class=\"\" data-state=\"closed\"><a class=\"decorated-link\" href=\"https:\/\/scholars.mssm.edu\/en\/publications\/a-foundational-transformer-leveraging-full-night-multichannel-sle\/?utm_source=chatgpt.com\" target=\"_blank\" rel=\"noopener\">A foundational transformer leveraging full night, multichannel sleep study data accurately classifies sleep stages<\/a><\/span><\/span><strong data-start=\"3366\" data-end=\"3476\">. (Aug 2025) B Fox, J Jiang, S Wickramaratne, P Kovatch, M Suarez-Farinas, NA Shah, A Parekh, GN Nadkarni.<\/strong><br data-start=\"3476\" data-end=\"3479\" \/><em data-start=\"3481\" data-end=\"3524\">Sleep, 48(8). DOI: 10.1093\/sleep\/zsaf061.<\/em><\/li>\n<li><span class=\"contents\" data-content-reference-start=\"4174\" data-content-reference-end=\"4292\"><span class=\"\" data-state=\"closed\"><a class=\"decorated-link\" href=\"https:\/\/www.nature.com\/articles\/s41746-025-01709-9?utm_source=chatgpt.com\" target=\"_blank\" rel=\"noopener\">A distributional reinforcement learning model for optimal glucose control after cardiac surgery<\/a><\/span><\/span><strong data-start=\"3621\" data-end=\"3984\">. (May 2025) JM Desman, ZW Hong, M Sabounchi, AS Sawant, J Gill, AC Costa, G Kumar, R Sharma, A Gupta, P McCarthy, V Nandwani, D Powell, A Carideo, D Goodwin, S Ahmed, U Gidwani, MA Levin, R Varghese, F Filsoufi, R Freeman, A Shetreat-Klein, AW Charney, I Hofer, L Chan, D Reich, P Kovatch, R Kohli-Seth, M Kraft, P Agrawal, JA Kellum, GN Nadkarni, A Sakhuja.<\/strong><br data-start=\"3984\" data-end=\"3987\" \/><em data-start=\"3989\" data-end=\"4053\">npj Digital Medicine, 8, 313. DOI: 10.1038\/s41746-025-01709-9.<\/em><\/li>\n<li><span class=\"contents\" data-content-reference-start=\"4796\" data-content-reference-end=\"4925\"><span class=\"\" data-state=\"closed\"><a class=\"decorated-link\" href=\"https:\/\/pubmed.ncbi.nlm.nih.gov\/40398851\/?utm_source=chatgpt.com\" target=\"_blank\" rel=\"noopener\">Summarize-then-Prompt: A Novel Prompt Engineering Strategy for Generating High-Quality Discharge Summaries<\/a><\/span><\/span><strong data-start=\"4171\" data-end=\"4333\">. (May\/Aug 2025) E Klang, J Gill, A Sharma, E Leibner, M Sabounchi, R Freeman, R Kohli-Seth, P Kovatch, AW Charney, L Stump, DL Reich, GN Nadkarni, A Sakhuja.<\/strong><br data-start=\"4333\" data-end=\"4336\" \/><em data-start=\"4338\" data-end=\"4432\">Applied Clinical Informatics, 16(4), 1325\u20131331. DOI: 10.1055\/a-2617-6572. Epub May 21, 2025.<\/em><\/li>\n<li><a id=\"menur70b\" class=\"fui-Link ___1q1shib f2hkw1w f3rmtva f1ewtqcl fyind8e f1k6fduh f1w7gpdv fk6fouc fjoy568 figsok6 f1s184ao f1mk8lai fnbmjn9 f1o700av f13mvf36 f1cmlufx f9n3di6 f1ids18y f1tx3yz7 f1deo86v f1eh06m1 f1iescvh fhgqx19 f1olyrje f1p93eir f1nev41a f1h8hb77 f1lqvz6u f10aw75t fsle3fq f17ae5zn\" title=\"https:\/\/scholars.mssm.edu\/en\/publications\/derivation-external-and-clinical-validation-of-a-deep-learning-ap\" href=\"https:\/\/scholars.mssm.edu\/en\/publications\/derivation-external-and-clinical-validation-of-a-deep-learning-ap\" target=\"_blank\" rel=\"noreferrer noopener\" aria-label=\"Link Derivation, external and clinical validation of a deep learning approach for detecting intracranial hypertension\">Derivation, external and clinical validation of a deep learning approach for detecting intracranial hypertension<\/a>. (Dec 2024) F Gulamali, P Jayaraman, P Kovatch, GN Nadkarni, et. al.<\/li>\n<li><a id=\"menur724\" class=\"fui-Link ___1q1shib f2hkw1w f3rmtva f1ewtqcl fyind8e f1k6fduh f1w7gpdv fk6fouc fjoy568 figsok6 f1s184ao f1mk8lai fnbmjn9 f1o700av f13mvf36 f1cmlufx f9n3di6 f1ids18y f1tx3yz7 f1deo86v f1eh06m1 f1iescvh fhgqx19 f1olyrje f1p93eir f1nev41a f1h8hb77 f1lqvz6u f10aw75t fsle3fq f17ae5zn\" title=\"https:\/\/scholars.mssm.edu\/en\/publications\/measurement-of-circulating-viral-antigens-post-sars-cov-2-infecti\" href=\"https:\/\/scholars.mssm.edu\/en\/publications\/measurement-of-circulating-viral-antigens-post-sars-cov-2-infecti\" target=\"_blank\" rel=\"noreferrer noopener\" aria-label=\"Link Measurement of circulating viral antigens post-SARS-CoV-2 infection in a multicohort study\">Measurement of circulating viral antigens post-SARS-CoV-2 infection in a multicohort study<\/a>. (Dec 2024) Z Swank, E Borberg, P Kovatch, TF Bumol, et. al.<\/li>\n<li><a id=\"menur72d\" class=\"fui-Link ___1q1shib f2hkw1w f3rmtva f1ewtqcl fyind8e f1k6fduh f1w7gpdv fk6fouc fjoy568 figsok6 f1s184ao f1mk8lai fnbmjn9 f1o700av f13mvf36 f1cmlufx f9n3di6 f1ids18y f1tx3yz7 f1deo86v f1eh06m1 f1iescvh fhgqx19 f1olyrje f1p93eir f1nev41a f1h8hb77 f1lqvz6u f10aw75t fsle3fq f17ae5zn\" title=\"https:\/\/scholars.mssm.edu\/en\/publications\/multimodal-fusion-learning-for-long-qt-syndrome-pathogenic-genoty\" href=\"https:\/\/scholars.mssm.edu\/en\/publications\/multimodal-fusion-learning-for-long-qt-syndrome-pathogenic-genoty\" target=\"_blank\" rel=\"noreferrer noopener\" aria-label=\"Link Multimodal fusion learning for long QT syndrome pathogenic genotypes in a racially diverse population\">Multimodal fusion learning for long QT syndrome pathogenic genotypes in a racially diverse population<\/a>. (Dec 2024) J Jiang, HM Thi Vy, P Kovatch, GN Nadkarni, et. al.<\/li>\n<li><a id=\"menur719\" class=\"fui-Link ___1q1shib f2hkw1w f3rmtva f1ewtqcl fyind8e f1k6fduh f1w7gpdv fk6fouc fjoy568 figsok6 f1s184ao f1mk8lai fnbmjn9 f1o700av f13mvf36 f1cmlufx f9n3di6 f1ids18y f1tx3yz7 f1deo86v f1eh06m1 f1iescvh fhgqx19 f1olyrje f1p93eir f1nev41a f1h8hb77 f1lqvz6u f10aw75t fsle3fq f17ae5zn\" title=\"https:\/\/scholars.mssm.edu\/en\/publications\/local-large-language-models-for-privacy-preserving-accelerated-re\" href=\"https:\/\/scholars.mssm.edu\/en\/publications\/local-large-language-models-for-privacy-preserving-accelerated-re\" target=\"_blank\" rel=\"noreferrer noopener\" aria-label=\"Link Local large language models for privacy-preserving accelerated review of historic echocardiogram reports\">Local large language models for privacy-preserving accelerated review of historic echocardiogram reports<\/a>. (Sept 2024) A Vaid, SQ Duong, P Kovatch, GN Nadkarni, et. al.<\/li>\n<li><a id=\"menur6vj\" class=\"fui-Link ___1q1shib f2hkw1w f3rmtva f1ewtqcl fyind8e f1k6fduh f1w7gpdv fk6fouc fjoy568 figsok6 f1s184ao f1mk8lai fnbmjn9 f1o700av f13mvf36 f1cmlufx f9n3di6 f1ids18y f1tx3yz7 f1deo86v f1eh06m1 f1iescvh fhgqx19 f1olyrje f1p93eir f1nev41a f1h8hb77 f1lqvz6u f10aw75t fsle3fq f17ae5zn\" title=\"https:\/\/scholars.mssm.edu\/en\/publications\/a-novel-method-leveraging-time-series-data-to-improve-subphenotyp\" href=\"https:\/\/scholars.mssm.edu\/en\/publications\/a-novel-method-leveraging-time-series-data-to-improve-subphenotyp\" target=\"_blank\" rel=\"noreferrer noopener\" aria-label=\"Link A novel method leveraging time series data to improve subphenotyping and application in critically ill patients with COVID-19\">A novel method leveraging time series data to improve subphenotyping and application in critically ill patients with COVID-19.<\/a> (Feb 2024) by W Oh, P Jayaraman, P Kovatch, and GN Nadkarni, et. al.<\/li>\n<li><a id=\"menur6v1\" class=\"fui-Link ___1q1shib f2hkw1w f3rmtva f1ewtqcl fyind8e f1k6fduh f1w7gpdv fk6fouc fjoy568 figsok6 f1s184ao f1mk8lai fnbmjn9 f1o700av f13mvf36 f1cmlufx f9n3di6 f1ids18y f1tx3yz7 f1deo86v f1eh06m1 f1iescvh fhgqx19 f1olyrje f1p93eir f1nev41a f1h8hb77 f1lqvz6u f10aw75t fsle3fq f17ae5zn\" title=\"https:\/\/scholars.mssm.edu\/en\/publications\/ninth-computational-approaches-for-cancer-workshop-cafcw23\" href=\"https:\/\/scholars.mssm.edu\/en\/publications\/ninth-computational-approaches-for-cancer-workshop-cafcw23\" target=\"_blank\" rel=\"noreferrer noopener\" aria-label=\"Link Ninth Computational Approaches for Cancer Workshop (CAFCW23)\">Ninth Computational Approaches for Cancer Workshop (CAFCW23)<\/a> (Nov 2023) by E Stahlberg, P Kovatch, L Borkon, et. al.<\/li>\n<li><a id=\"menur6tt\" class=\"fui-Link ___1q1shib f2hkw1w f3rmtva f1ewtqcl fyind8e f1k6fduh f1w7gpdv fk6fouc fjoy568 figsok6 f1s184ao f1mk8lai fnbmjn9 f1o700av f13mvf36 f1cmlufx f9n3di6 f1ids18y f1tx3yz7 f1deo86v f1eh06m1 f1iescvh fhgqx19 f1olyrje f1p93eir f1nev41a f1h8hb77 f1lqvz6u f10aw75t fsle3fq f17ae5zn\" title=\"https:\/\/scholars.mssm.edu\/en\/publications\/implications-of-the-use-of-artificial-intelligence-predictive-mod\" href=\"https:\/\/scholars.mssm.edu\/en\/publications\/implications-of-the-use-of-artificial-intelligence-predictive-mod\" target=\"_blank\" rel=\"noreferrer noopener\" aria-label=\"Link Implications of the Use of Artificial Intelligence Predictive Models in Health Care Settings\">Implications of the Use of Artificial Intelligence Predictive Models in Health Care Settings<\/a>. (Oct 2023) by A Vaid, A Sawant, P Kovatch, GN Nadkarni, et. al.<\/li>\n<li><a id=\"menur6va\" class=\"fui-Link ___1q1shib f2hkw1w f3rmtva f1ewtqcl fyind8e f1k6fduh f1w7gpdv fk6fouc fjoy568 figsok6 f1s184ao f1mk8lai fnbmjn9 f1o700av f13mvf36 f1cmlufx f9n3di6 f1ids18y f1tx3yz7 f1deo86v f1eh06m1 f1iescvh fhgqx19 f1olyrje f1p93eir f1nev41a f1h8hb77 f1lqvz6u f10aw75t fsle3fq f17ae5zn\" title=\"https:\/\/scholars.mssm.edu\/en\/publications\/returning-integrated-genomic-risk-and-clinical-recommendations-th\" href=\"https:\/\/scholars.mssm.edu\/en\/publications\/returning-integrated-genomic-risk-and-clinical-recommendations-th\" target=\"_blank\" rel=\"noreferrer noopener\" aria-label=\"Link Returning integrated genomic risk and clinical recommendations: The eMERGE study\">Returning integrated genomic risk and clinical recommendations: The eMERGE study<\/a>. (Apr 2023) by eMERGE Consortium, P Kovatch, et. al.<\/li>\n<li><a id=\"menur6rl\" class=\"fui-Link ___1q1shib f2hkw1w f3rmtva f1ewtqcl fyind8e f1k6fduh f1w7gpdv fk6fouc fjoy568 figsok6 f1s184ao f1mk8lai fnbmjn9 f1o700av f13mvf36 f1cmlufx f9n3di6 f1ids18y f1tx3yz7 f1deo86v f1eh06m1 f1iescvh fhgqx19 f1olyrje f1p93eir f1nev41a f1h8hb77 f1lqvz6u f10aw75t fsle3fq f17ae5zn\" title=\"https:\/\/scholars.mssm.edu\/en\/publications\/autoencoders-for-sample-size-estimation-for-fully-connected-neura\" href=\"https:\/\/scholars.mssm.edu\/en\/publications\/autoencoders-for-sample-size-estimation-for-fully-connected-neura\" target=\"_blank\" rel=\"noreferrer noopener\" aria-label=\"Link Autoencoders for sample size estimation for fully connected neural network classifiers\">Autoencoders for sample size estimation for fully connected neural network classifiers. <\/a>\u00a0(Dec 2022) by F Gulamali, AS Sawant, P Kovatch, A Charney, GN Nadkarni, et. al.<\/li>\n<li><a href=\"https:\/\/pubmed.ncbi.nlm.nih.gov\/35958514\/\">Quantitative chest computed tomography combined with plasma cytokines predict outcomes in COVID-19 patients<\/a> (August 2022) by P. Kovatch, S. Nirenberg, M. Merad, S. Gnjatic, et al.<\/li>\n<li><a href=\"https:\/\/cjasn.asnjournals.org\/content\/17\/7\/1017\">Automated Determination of Left Ventricular Function Using Electrocardiogram Data in Patients on Maintenance Hemodialysis<\/a> (July 2022) by P. Kovatch, A. Charney, G. Nadkarni, et al.<\/li>\n<li><a href=\"https:\/\/doi.org\/10.21203\/rs.3.rs-1055587\/v1\">Multi-ethnic Investigation of Risk and Immune Determinants of COVID-19 Outcomes<\/a> (March 2022) by P. Kovatch, S. Nirenberg, et al.<\/li>\n<li><a id=\"menur6sd\" class=\"fui-Link ___1q1shib f2hkw1w f3rmtva f1ewtqcl fyind8e f1k6fduh f1w7gpdv fk6fouc fjoy568 figsok6 f1s184ao f1mk8lai fnbmjn9 f1o700av f13mvf36 f1cmlufx f9n3di6 f1ids18y f1tx3yz7 f1deo86v f1eh06m1 f1iescvh fhgqx19 f1olyrje f1p93eir f1nev41a f1h8hb77 f1lqvz6u f10aw75t fsle3fq f17ae5zn\" title=\"https:\/\/scholars.mssm.edu\/en\/publications\/functional-effects-of-cardiomyocyte-injury-in-covid-19-2\" href=\"https:\/\/scholars.mssm.edu\/en\/publications\/functional-effects-of-cardiomyocyte-injury-in-covid-19-2\" target=\"_blank\" rel=\"noreferrer noopener\" aria-label=\"Link Functional Effects of Cardiomyocyte Injury in COVID-19\">Functional Effects of Cardiomyocyte Injury in COVID-19<\/a>. (Jan 2022) by M Siddiq, AT Chan, P Kovatch, R Iyengar., et. al.<\/li>\n<li><a href=\"https:\/\/doi.org\/10.1093\/jamia\/ocab252\">Using sequence clustering to identify clinically relevant subphenotypes in patients with COVID-19 admitted to the intensive care unit<\/a> (Jan 2022) by P. Kovatch, A. Charney, G. Nadkarni, et al.<\/li>\n<li><a href=\"https:\/\/doi.org\/10.1101\/2021.10.11.21264709\">Quantitative chest CT combined with plasma cytokines predict outcomes in COVID-19 patients<\/a> (Oct 2021) by P. Kovatch, et al.<\/li>\n<li><a href=\"https:\/\/doi.org\/10.2215\/CJN.17311120\">Predictive Approaches for Acute Dialysis Requirement and Death in COVID-19<\/a> (Aug 2021) by P. Kovatch, A. Vaid et al.<\/li>\n<li><a href=\"https:\/\/doi.org\/10.1038\/s41598-021-93126-7\">Prediction of individual COVID-19 diagnosis using baseline demographics and lab data<\/a> (July 2021) by P. Kovatch, J. Zhang et al.<\/li>\n<li><a href=\"https:\/\/doi.org\/10.1101\/2021.07.25.21261105\">Development of a federated learning approach to predict acute kidney injury in adult hospitalized patients with COVID-19 in New York City<\/a> (July 2021) by P. Kovatch, S. K. Jaladanki et al.<\/li>\n<li><a href=\"https:\/\/www.nature.com\/articles\/s43856-021-00006-2\">Analysis of sex-specific risk factors and clinical outcomes in COVID-19<\/a> (June 2021) by P. Kovatch, S. Nirenberg, et al.<\/li>\n<li><a href=\"https:\/\/doi.org\/10.2215\/CJN.12360720\">Outcomes of Patients on Maintenance Dialysis Hospitalized with COVID-19<\/a> (March 2021) by P. Kovatch, L. Chan et al.<\/li>\n<li><a href=\"https:\/\/doi.org\/10.1038\/s41436-020-01063-z\">GU\u00cdA: a digital platform to facilitate result disclosure in genetic counseling<\/a> (Feb 2021) by P. Kovatch, S. A. Suckiel et al.<\/li>\n<li><a href=\"https:\/\/doi.org\/10.1186\/s13063-020-04953-4\">The NYCKidSeq project: study protocol for a randomized controlled trial incorporating genomics into the clinical care of New York City children<\/a> (Jan 2021) by P. Kovatch, J. A. Odgis et al.<\/li>\n<li><a href=\"https:\/\/doi.org\/10.1101\/2020.11.10.20229294\">Physiology of cardiomyocyte injury in COVID-19<\/a> (Nov 2020) by P. Kovatch, M. M. Siddiq et al.<\/li>\n<li><a href=\"10.2196\/24018\">Machine Learning to Predict Mortality and Critical Events in COVID-19 Positive New York City Patients<\/a> (Nov 2020) by P. Kovatch, A. Vaid et al.<\/li>\n<li><a href=\"10.1136\/bmjopen-2020-040736\">Retrospective cohort study of clinical characteristics of 2199 hospitalised patients with COVID-19 in New York City<\/a> (Nov 2020) by P. Kovatch, I. Paranjpe et al.<\/li>\n<li><a href=\"https:\/\/doi.org\/10.1038\/s41591-020-1051-9\">An inflammatory cytokine signature predicts COVID-19 severity and survival<\/a> (Oct 2020) by P. Kovatch, D. M. Del Valle et al.<\/li>\n<li><a href=\"10.1136\/bmjopen-2020-040441\">Hospitalised COVID-19 patients of the Mount Sinai Health System: a retrospective observational study using the electronic medical records<\/a> (Oct 2020) by P. Kovatch, Z. Wang et al.<\/li>\n<li><a href=\"https:\/\/sc20.supercomputing.org\/2020\/08\/11\/covid-cancer-and-hpc-highlight-the-computational-approaches-for-cancer-workshop-at-sc\/\">COVID, Cancer, and HPC Highlight the Computational Approaches for Cancer Workshop at SC<\/a> (Aug 2020) through SC20<\/li>\n<li><a href=\"https:\/\/www.ncbi.nlm.nih.gov\/pmc\/articles\/PMC7575271\/\">Optimizing High-Performance Computing Systems for Biomedical Workloads<\/a> (July 2020) by P. Kovatch et al.<\/li>\n<li><a href=\"https:\/\/doi.org\/10.1101\/2020.05.28.20115758\">An inflammatory cytokine signature helps predict COVID-19 severity and death<\/a> (May 2020) by P. Kovatch, D. M. Del Valle et al.<\/li>\n<li><a href=\"https:\/\/doi.org\/10.1186\/s12911-018-0653-3\">Pharmacological risk factors associated with hospital readmission rates in a psychiatric cohort identified using prescriptome data mining<\/a> (Sept 2018), P. Kovatch, K. Shameer et al.<\/li>\n<li><a href=\"10.1097\/MOP.0000000000000467\">Big and disparate data: considerations for pediatric consortia<\/a> (April 2017) by P. Kovatch, J. A. Stingone et al.<\/li>\n<li><a href=\"https:\/\/www.ascb.org\/careers\/preserving-data-whos-got-your-backup\/\">Preserving Data: Who\u2019s Got Your Back(up)?<\/a> (Feb 2016) through ACSB: An International Forum for Cell Biology<\/li>\n<li><a href=\"10.1142\/9789813207813_0027\">Predictive modeling of hospital readmission rates using electronic medical record-wide machine learning: a case-study using Mount Sinai heart failure cohort<\/a> (2016) by P. Kovatch, K. Shameer et al.<\/li>\n<li><a href=\"https:\/\/bmcmedinformdecismak.biomedcentral.com\/articles\/10.1186\/s12911-018-0653-3\">Pharmacological factors associated with congestive heart failure hospital readmission: a case-study using 15,768 heart failure patients from two health systems<\/a> (2016) by P. Kovatch, K. Johnson et al.<\/li>\n<li>Accelerating child health exposure research with the CHEAR data center (Oct 2016) by P. Kovatch, D.L. McGuinness et al.<\/li>\n<li>Lessons learned from the Children\u2019s Health Exposure Analysis Resource (CHEAR) data center (Aug 2016) by P. Kovatch, D.L. McGuinness et al.<\/li>\n<li><a href=\"https:\/\/doi.org\/10.1145\/2807591.2807595\">Big Omics Data Experience<\/a> (Nov 2015) by P. Kovatch et al.<\/li>\n<li><a href=\"https:\/\/dl.acm.org\/doi\/abs\/10.1109\/Grid.2011.41\">Improved grid security posture through multi-factor authentication<\/a> (Sept 2011) by P. Kovatch, V. Hazelwood et al.<\/li>\n<li><a href=\"https:\/\/link.springer.com\/chapter\/10.1007\/978-3-642-29740-3_25\">The Malthusian catastrophe is upon us! Are the largest HPC machines ever up?<\/a> (Aug 2011) by P. Kovatch et al.<\/li>\n<li><a href=\"https:\/\/cug.org\/5-publications\/proceedings_attendee_lists\/CUG11CD\/pages\/1-program\/final_program\/Thursday\/17A-Whitt-Paper.pdf\">Increasing petascale resource utilization through bimodal scheduling policies<\/a> (May 2011) by P. Kovatch, P. Andrews et al.<\/li>\n<li><a href=\"http:\/\/dx.doi.org\/10.1109\/HiPC.2011.6152723\">Scheduling diverse high performance computing systems with the goal of maximizing utilization<\/a> (Feb 2011) by P. Kovatch, T. Samuel et al.<\/li>\n<\/ul>\n<p>\u00a0<\/p>\n<p>[\/et_pb_text][et_pb_button button_url=&#8221;https:\/\/labs.icahn.mssm.edu\/minervalab\/publications\/&#8221; button_text=&#8221;Return to Publications&#8221; button_alignment=&#8221;center&#8221; _builder_version=&#8221;4.9.0&#8243; _module_preset=&#8221;default&#8221; custom_button=&#8221;on&#8221; button_text_color=&#8221;#FFFFFF&#8221; button_bg_use_color_gradient=&#8221;on&#8221; button_bg_color_gradient_start=&#8221;#00aeef&#8221; button_bg_color_gradient_end=&#8221;#221f72&#8243; button_bg_color_gradient_direction=&#8221;264deg&#8221; button_border_width=&#8221;0px&#8221; button_border_radius=&#8221;26px&#8221; button_font=&#8221;|600||on|||||&#8221; button_use_icon=&#8221;off&#8221; custom_padding=&#8221;15px|30px|15px|30px|false|false&#8221; button_bg_color_gradient_stops=&#8221;#00aeef 0%|#221f72 100%&#8221;]<\/p>\n<p><\/p>\n<p>[\/et_pb_button][\/et_pb_column][\/et_pb_row][\/et_pb_section]<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Scientific Computing and Data\u00a0\/\u00a0High Performance Computing\u00a0\/ Publications \/ Kovatch Publications Publications Authored &amp; Co-Authored by Patricia Kovatch, Dean of Scientific Computing and DataContrastive Transformer-Driven Discovery of Temporal Hemodynamic Subphenotypes in Cardiac Surgery Patients. (Mar 2026) JM Desman, M Sabounchi, W Oh, G Kumar, \u2026 P Kovatch, \u2026 GN Nadkarni, A Sakhuja. Preprint.Evaluating Sycophancy in Frontier [&hellip;]<\/p>\n","protected":false},"author":600,"featured_media":0,"parent":2288,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_et_pb_use_builder":"on","_et_pb_old_content":"<p><strong>Authored & Co-Authored by Patricia Kovatch, Dean of Scientific Computing and Data<\/strong><\/p><ol><li><a href=\"https:\/\/doi.org\/10.2215\/CJN.17311120\">Predictive Approaches for Acute Dialysis Requirement and Death in COVID-19<\/a> (Aug 2021) by P. Kovatch, A. Vaid et al.<\/li><li><a href=\"https:\/\/doi.org\/10.1038\/s41598-021-93126-7\">Prediction of individual COVID-19 diagnosis using baseline demographics and lab data<\/a> (July 2021) by P. Kovatch, J. Zhang et al.<\/li><li><a href=\"https:\/\/doi.org\/10.1101\/2021.07.25.21261105\">Development of a federated learning approach to predict acute kidney injury in adult hospitalized patients with COVID-19 in New York City<\/a> (July 2021) by P. Kovatch, S. K. Jaladanki et al.<\/li><li><a href=\"https:\/\/doi.org\/10.2215\/CJN.12360720\">Outcomes of Patients on Maintenance Dialysis Hospitalized with COVID-19<\/a> (March 2021) by P. Kovatch, L. Chan et al.<\/li><li><a href=\"https:\/\/doi.org\/10.1038\/s41436-020-01063-z\">GU\u00cdA: a digital platform to facilitate result disclosure in genetic counseling<\/a> (Feb 2021) by P. Kovatch, S. A. Suckiel et al.<\/li><li><a href=\"https:\/\/doi.org\/10.1186\/s13063-020-04953-4\">The NYCKidSeq project: study protocol for a randomized controlled trial incorporating genomics into the clinical care of diverse New York City children<\/a> (Jan 2021) by P. Kovatch, J. A. Odgis et al.<\/li><li><a href=\"https:\/\/doi.org\/10.1101\/2020.11.10.20229294\">Physiology of cardiomyocyte injury in COVID-19<\/a> (Nov 2020) by P. Kovatch, M. M. Siddiq et al.<\/li><li><a href=\"10.2196\/24018\">Machine Learning to Predict Mortality and Critical Events in COVID-19 Positive New York City Patients<\/a> (Nov 2020) by P. Kovatch, A. Vaid et al.<\/li><li><a href=\"10.1136\/bmjopen-2020-040736\">Retrospective cohort study of clinical characteristics of 2199 hospitalised patients with COVID-19 in New York City<\/a> (Nov 2020) by P. Kovatch, I. Paranjpe et al.<\/li><li><a href=\"https:\/\/doi.org\/10.1038\/s41591-020-1051-9\">An inflammatory cytokine signature predicts COVID-19 severity and survival<\/a> (Oct 2020) by P. Kovatch, D. M. Del Valle et al.<\/li><li><a href=\"10.1136\/bmjopen-2020-040441\">Hospitalised COVID-19 patients of the Mount Sinai Health System: a retrospective observational study using the electronic medical records<\/a> (Oct 2020) by P. Kovatch, Z. Wang et al.<\/li><li><a href=\"https:\/\/sc20.supercomputing.org\/2020\/08\/11\/covid-cancer-and-hpc-highlight-the-computational-approaches-for-cancer-workshop-at-sc\/\">COVID, Cancer, and HPC Highlight the Computational Approaches for Cancer Workshop at SC<\/a> (Aug 2020) through SC20<\/li><li><a href=\"https:\/\/www.ncbi.nlm.nih.gov\/pmc\/articles\/PMC7575271\/\">Optimizing High-Performance Computing Systems for Biomedical Workloads<\/a> (July 2020) by P. Kovatch et al.<\/li><li><a href=\"https:\/\/doi.org\/10.1101\/2020.05.28.20115758\">An inflammatory cytokine signature helps predict COVID-19 severity and death<\/a> (May 2020) by P. Kovatch, D. M. Del Valle et al.<\/li><li><a href=\"10.1109\/ipdpsw50202.2020.00040\">Optimizing High-Performance Computing Systems for Biomedical Workloads<\/a> (May 2020) by P. Kovatch<\/li><li><a href=\"https:\/\/doi.org\/10.1186\/s12911-018-0653-3\">Pharmacological risk factors associated with hospital readmission rates in a psychiatric cohort identified using prescriptome data mining<\/a> (Sept 2018), P. Kovatch, K. Shameer et al.<\/li><li><a href=\"10.1097\/MOP.0000000000000467\">Big and disparate data: considerations for pediatric consortia<\/a> (April 2017) by P. Kovatch, J. A. Stingone et al.<\/li><li><a href=\"https:\/\/www.ascb.org\/careers\/preserving-data-whos-got-your-backup\/\">Preserving Data: Who\u2019s Got Your Back(up)?<\/a> (Feb 2016) through ACSB: An International Forum for Cell Biology<\/li><li><a href=\"10.1142\/9789813207813_0027\">Predictive modeling of hospital readmission rates using electronic medical record-wide machine learning: a case-study using Mount Sinai heart failure cohort<\/a> (2016) by P. Kovatch, K. Shameer et al.<\/li><li><a href=\"https:\/\/bmcmedinformdecismak.biomedcentral.com\/articles\/10.1186\/s12911-018-0653-3\">Pharmacological factors associated with congestive heart failure hospital readmission: a case-study using 15,768 heart failure patients from two health systems<\/a> (2016) by P. Kovatch, K. Johnson et al.<\/li><li>Accelerating child health exposure research with the CHEAR data center (Oct 2016) by P. Kovatch, D.L. McGuinness et al.<\/li><li>Lessons learned from the Children\u2019s Health Exposure Analysis Resource (CHEAR) data center (Aug 2016) by P. Kovatch, D.L. McGuinness et al.<\/li><li><a href=\"https:\/\/doi.org\/10.1145\/2807591.2807595\">Big Omics Data Experience<\/a> (Nov 2015) by P. Kovatch et al.<\/li><li><a href=\"https:\/\/dl.acm.org\/doi\/abs\/10.1109\/Grid.2011.41\">Improved grid security posture through multi-factor authentication<\/a> (Sept 2011) by P. Kovatch, V. Hazelwood et al.<\/li><li><a href=\"https:\/\/link.springer.com\/chapter\/10.1007\/978-3-642-29740-3_25\">The Malthusian catastrophe is upon us! Are the largest HPC machines ever up?<\/a> (Aug 2011) by P. Kovatch et al.<\/li><li><a href=\"https:\/\/cug.org\/5-publications\/proceedings_attendee_lists\/CUG11CD\/pages\/1-program\/final_program\/Thursday\/17A-Whitt-Paper.pdf\">Increasing petascale resource utilization through bimodal scheduling policies<\/a> (May 2011) by P. Kovatch, P. Andrews et al.<\/li><li><a href=\"http:\/\/dx.doi.org\/10.1109\/HiPC.2011.6152723\">Scheduling diverse high performance computing systems with the goal of maximizing utilization<\/a> (Feb 2011) by P. Kovatch, T. Samuel et al.<\/li><\/ol><p>\u00a0<\/p>","_et_gb_content_width":"","footnotes":""},"class_list":["post-2269","page","type-page","status-publish","hentry"],"aioseo_notices":[],"_links":{"self":[{"href":"https:\/\/labs.icahn.mssm.edu\/minervalab\/wp-json\/wp\/v2\/pages\/2269","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/labs.icahn.mssm.edu\/minervalab\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/labs.icahn.mssm.edu\/minervalab\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/labs.icahn.mssm.edu\/minervalab\/wp-json\/wp\/v2\/users\/600"}],"replies":[{"embeddable":true,"href":"https:\/\/labs.icahn.mssm.edu\/minervalab\/wp-json\/wp\/v2\/comments?post=2269"}],"version-history":[{"count":25,"href":"https:\/\/labs.icahn.mssm.edu\/minervalab\/wp-json\/wp\/v2\/pages\/2269\/revisions"}],"predecessor-version":[{"id":15125,"href":"https:\/\/labs.icahn.mssm.edu\/minervalab\/wp-json\/wp\/v2\/pages\/2269\/revisions\/15125"}],"up":[{"embeddable":true,"href":"https:\/\/labs.icahn.mssm.edu\/minervalab\/wp-json\/wp\/v2\/pages\/2288"}],"wp:attachment":[{"href":"https:\/\/labs.icahn.mssm.edu\/minervalab\/wp-json\/wp\/v2\/media?parent=2269"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}