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aihc-programs [2025/12/12 10:29]
nigam [Efforts in SOM] |
aihc-programs [2026/09/13 14:23] (current)
nigam [Efforts in SOE] |
| - [[https://spezi.sites.stanford.edu/|Spezi ]] by Stanford Biodesign Digital Health, is an open-source framework for the rapid development of modern, interoperable digital health applications based on an ecosystem of modules that exchange data using health data standards such as HL7® FHIR®. | - [[https://spezi.sites.stanford.edu/|Spezi ]] by Stanford Biodesign Digital Health, is an open-source framework for the rapid development of modern, interoperable digital health applications based on an ecosystem of modules that exchange data using health data standards such as HL7® FHIR®. |
| - [[https://innovations.stanford.edu/about|Stanford Healthcare Innovation Lab]], which characterizes an individual’s healthy baseline to identify when deviations from baseline occur and intervene to maintain health as well as early detection and prevention of disease. | - [[https://innovations.stanford.edu/about|Stanford Healthcare Innovation Lab]], which characterizes an individual’s healthy baseline to identify when deviations from baseline occur and intervene to maintain health as well as early detection and prevention of disease. |
| | - [[https://heal-ai.stanford.edu/ | Heal-AI]], Healthcare Ethical Assessment Lab for Artificial Intelligence, works to identify and address ethical issues arising from use of healthcare AI tools before they become problems for the organization, clinicians, and patients. |
| | - [[https://guide-ai.stanford.edu/ | GUIDE-AI]], works on projects that provide Guidance for the Use, Implementation, Development, and Evaluation of Healthcare AI at SHC. |
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| - [[https://aihealth.stanford.edu/|AI for Health]], with the mission to develop unbiased, explainable AI algorithms to better understand health and wellness, to improve the efficiency, value and delivery of healthcare and to improve patient experience and outcomes. | - [[https://aihealth.stanford.edu/|AI for Health]], with the mission to develop unbiased, explainable AI algorithms to better understand health and wellness, to improve the efficiency, value and delivery of healthcare and to improve patient experience and outcomes. |
| - [[https://aimi.stanford.edu/research/ai-healthcare-bootcamp |AI for Healthcare Bootcamp]], which provides an opportunity to do cutting-edge research at the intersection of AI and healthcare. | - [[https://aimi.stanford.edu/research/ai-healthcare-bootcamp |AI for Healthcare Bootcamp]], which provides an opportunity to do cutting-edge research at the intersection of AI and healthcare. |
| | - [[https://aimslab.stanford.edu/ | AI Measurement Science]], which is a community building the methods, courses, and software to close the measurement gap. |
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| ==== Efforts at SHC ==== | ==== Efforts at SHC ==== |
