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What is AIR\u00b7MS?<\/strong><\/span><\/h1>\nPatient 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>\n
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>\n
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>\n
![\"\"](\"https:\/\/labs.icahn.mssm.edu\/minervalab\/wp-content\/uploads\/sites\/342\/2025\/09\/AIRMS-HANA-Architecture-ABOUT-PAGE-1.png\")
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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?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). […]<\/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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