[et_pb_section fb_built=”1″ _builder_version=”4.9.0″ _module_preset=”default”][et_pb_row _builder_version=”4.9.0″ _module_preset=”default” custom_margin=”||0px||false|false” custom_padding=”||0px||false|false”][et_pb_column type=”4_4″ _builder_version=”4.9.0″ _module_preset=”default”][et_pb_text admin_label=”Title” _builder_version=”4.9.0″ _module_preset=”default”]<\/p>\n
[\/et_pb_text][et_pb_text _builder_version=”4.9.0″ _module_preset=”default” text_font_size=”18px”]<\/p>\n
AIR\u00b7MS differentiates itself from other research\u202fplatforms by leveraging the power of SAP HANA’s in-memory database. We offer features such as in-memory computing,\u202ffull text search over unstructured data (such as clinical notes), and Python SQL libraries\u202fto create patient cohorts over multi-modal health data.<\/p>\n
In addition, we are also utilizing the latest in cloud technologies, offering our users a secure yet agile\u202fenvironment.<\/p>\n
[\/et_pb_text][\/et_pb_column][\/et_pb_row][et_pb_row column_structure=”1_4,1_4,1_4,1_4″ _builder_version=”4.9.0″ _module_preset=”default” custom_margin=”||0px||false|false” custom_padding=”||0px||false|false”][et_pb_column type=”1_4″ _builder_version=”4.9.0″ _module_preset=”default”][et_pb_blurb title=”SAP HANA In-Memory Database” url=”https:\/\/labs.icahn.mssm.edu\/airms\/technology\/sap-hana-in-memory-database\/” url_new_window=”on” admin_label=”SAP Hana” _builder_version=”4.9.0″ _module_preset=”default” locked=”off”][\/et_pb_blurb][\/et_pb_column][et_pb_column type=”1_4″ _builder_version=”4.9.0″ _module_preset=”default”][et_pb_blurb title=”Secure Cloud Infrastructure” url=”https:\/\/labs.icahn.mssm.edu\/airms\/technology\/secure-cloud-infrastructure\/” url_new_window=”on” admin_label=”Cloud Infra” _builder_version=”4.9.0″ _module_preset=”default” locked=”off”][\/et_pb_blurb][\/et_pb_column][et_pb_column type=”1_4″ _builder_version=”4.9.0″ _module_preset=”default”][et_pb_blurb title=”Python Libraries” url=”https:\/\/labs.icahn.mssm.edu\/airms\/technology\/python-libraries\/” url_new_window=”on” admin_label=”Python” _builder_version=”4.9.0″ _module_preset=”default” locked=”off”][\/et_pb_blurb][\/et_pb_column][et_pb_column type=”1_4″ _builder_version=”4.9.0″ _module_preset=”default”][et_pb_blurb title=”Performance Highlights” admin_label=”Performance” _builder_version=”4.9.0″ _module_preset=”default” hover_enabled=”0″ locked=”off” url_new_window=”on” link_option_url=”https:\/\/labs.icahn.mssm.edu\/airms\/technology\/performance-highlights\/” sticky_enabled=”0″][\/et_pb_blurb][\/et_pb_column][\/et_pb_row][et_pb_row _builder_version=”4.9.0″ _module_preset=”default”][et_pb_column type=”4_4″ _builder_version=”4.9.0″ _module_preset=”default”][et_pb_divider color=”#58595B” _builder_version=”4.9.0″ _module_preset=”default” custom_margin=”0px||||false|false” custom_padding=”0px||||false|false”][\/et_pb_divider][et_pb_text admin_label=”Text” _builder_version=”4.9.0″ _module_preset=”default” text_font_size=”18px” locked=”off”]AIR\u00b7MS currently runs in the following approved computational environments:[\/et_pb_text][\/et_pb_column][\/et_pb_row][et_pb_row column_structure=”1_2,1_2″ _builder_version=”4.9.0″ _module_preset=”default” custom_margin=”0px||||false|false” custom_padding=”0px||||false|false”][et_pb_column type=”1_2″ _builder_version=”4.9.0″ _module_preset=”default”][et_pb_blurb title=”Azure Machine Learning (AML)” url=”https:\/\/azure.microsoft.com\/en-us\/products\/machine-learning\/” url_new_window=”on” admin_label=”AML” _builder_version=”4.9.0″ _module_preset=”default” locked=”off”][\/et_pb_blurb][\/et_pb_column][et_pb_column type=”1_2″ _builder_version=”4.9.0″ _module_preset=”default”][et_pb_blurb title=”High-Performance Computing (HPC)” url=”https:\/\/labs.icahn.mssm.edu\/minervalab\/about-us\/” url_new_window=”on” admin_label=”HPC” _builder_version=”4.9.0″ _module_preset=”default” locked=”off”][\/et_pb_blurb][\/et_pb_column][\/et_pb_row][\/et_pb_section]<\/p>\n","protected":false},"excerpt":{"rendered":"
TechnologyAIR\u00b7MS differentiates itself from other research\u202fplatforms by leveraging the power of SAP HANA’s in-memory database. We offer features such as in-memory computing,\u202ffull text search over unstructured data (such as clinical notes), and Python SQL libraries\u202fto create patient cohorts over multi-modal health data. In addition, we are also utilizing the latest in cloud technologies, offering our […]<\/p>\n","protected":false},"author":610,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_et_pb_use_builder":"on","_et_pb_old_content":"","_et_gb_content_width":"","footnotes":""},"class_list":["post-422","page","type-page","status-publish","hentry"],"aioseo_notices":[],"_links":{"self":[{"href":"https:\/\/labs.icahn.mssm.edu\/airms\/wp-json\/wp\/v2\/pages\/422","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/labs.icahn.mssm.edu\/airms\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/labs.icahn.mssm.edu\/airms\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/labs.icahn.mssm.edu\/airms\/wp-json\/wp\/v2\/users\/610"}],"replies":[{"embeddable":true,"href":"https:\/\/labs.icahn.mssm.edu\/airms\/wp-json\/wp\/v2\/comments?post=422"}],"version-history":[{"count":19,"href":"https:\/\/labs.icahn.mssm.edu\/airms\/wp-json\/wp\/v2\/pages\/422\/revisions"}],"predecessor-version":[{"id":788,"href":"https:\/\/labs.icahn.mssm.edu\/airms\/wp-json\/wp\/v2\/pages\/422\/revisions\/788"}],"wp:attachment":[{"href":"https:\/\/labs.icahn.mssm.edu\/airms\/wp-json\/wp\/v2\/media?parent=422"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}