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What is AIR\u00b7MS?<\/strong><\/span><\/h1>\nThe AI-Ready Mount Sinai (AIR\u00b7MS) platform contains patient data generated from the clinical care processes at the Mount Sinai Health System (MSHS). AIR\u00b7MS includes a high-performance SAP HANA (Systems, Applications and Products in Data Processing High-Performance Analytic Appliance) database with MSHS electronic health record (EHR) data in the OHDSI (Observational Health Data Sciences and Informatics) OMOP (Observational Medical Outcomes Partnership) data format. It also contains metadata from and links to raw data sets in other modalities, such as radiology, genomics and pathology. Researchers can access the data through direct database access, AI agents, cohort query tools and the high-performance computer, Minerva. Minerva contains >21 petaflops of theoretical computational power and MSHS clinical data from radiology, genomics, pathology and other modalities. An expert team of 20+ PhD\/MD computational scientists, biomedical informaticists and computer scientists, partner with researchers and clinicians to effectively and efficiently utilize these resources for translational science.<\/p>\n
![](\"https:\/\/labs.icahn.mssm.edu\/minervalab\/wp-content\/uploads\/sites\/342\/2026\/09\/AIR.MS-diagram.jpg\")
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\n\t\t\t\t\n\t\t\t\t\n\t\t\t\t\n\t\t\t\t\n\t\t\t\t\n\t\t\t<\/div> Scientific Computing and Data \/ AIR\u00b7MS (AI Ready Mount Sinai) \/ About Us What is AIR\u00b7MS?The AI-Ready Mount Sinai (AIR\u00b7MS) platform contains patient data generated from the clinical care processes at the Mount Sinai Health System (MSHS). AIR\u00b7MS includes a high-performance SAP HANA (Systems, Applications and Products in Data Processing High-Performance Analytic Appliance) database […]<\/p>\n","protected":false},"author":700,"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":"What is AIR\u2022MS?<\/h2>
Patient data generated from different clinical departments across Health Systems is often heavily siloed in different repositories and hard to access for research purposes. To address this challenge, HPI\u00b7MS and its partner Data4Life are developing AI-Ready Mount Sinai (AIR\u00b7MS). AIR\u00b7MS is a cloud-based, multi-modal health data platform that integrates this data.<\/p>
By creating an innovative environment in which highly skilled data scientists can access clinical data such as EHR, imaging, -omics, and sensor data, AIR\u00b7MS is facilitating easy access to a revolutionary unified data source that will accelerate the advancement of health-care-driven, AI-based solutions.<\/p>
This platform is equipped with state-of-the-art computational frameworks and architectures to enable rapid scientific discovery alongside translational applications into real-world clinical settings. Facilitating multi-modal data access within a large academic medical institution such as Mount Sinai is an enormous challenge but promises to greatly accelerate the application of clinical data in developing the next generation of health care systems.<\/p>
![\"\"](\"https:\/\/labs.icahn.mssm.edu\/minervalab\/wp-content\/uploads\/sites\/342\/2025\/08\/AI-Figure-300x169.jpg\")
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<\/p>\nWhat is AIR\u2022MS?<\/h2>
Patient data generated from different clinical departments across Health Systems is often heavily siloed in different repositories and hard to access for research purposes. To address this challenge, HPI\u00b7MS and its partner Data4Life are developing AI-Ready Mount Sinai (AIR\u00b7MS). AIR\u00b7MS is a cloud-based, multi-modal health data platform that integrates this data.<\/p>
By creating an innovative environment in which highly skilled data scientists can access clinical data such as EHR, imaging, -omics, and sensor data, AIR\u00b7MS is facilitating easy access to a revolutionary unified data source that will accelerate the advancement of health-care-driven, AI-based solutions.<\/p>
This platform is equipped with state-of-the-art computational frameworks and architectures to enable rapid scientific discovery alongside translational applications into real-world clinical settings. Facilitating multi-modal data access within a large academic medical institution such as Mount Sinai is an enormous challenge but promises to greatly accelerate the application of clinical data in developing the next generation of health care systems.<\/p>
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