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- | ====== Stanford Medicine Program for Artificial Intelligence in Healthcare | + | ~~REDIRECT> |
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- | Consider the case of Vera, a 60 year old woman of Asian descent with a history of hypertension and asthma, entering the doctor' | + | |
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- | However, without accurate risk-stratification to decide who to treat, and when, Vera's care remains reactive and suboptimal. Imagine how Vera’s experience would change if we could predict risks of specific events and take proactive action. | + | |
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- | ====== Our efforts ====== | + | |
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- | We are working on a set of efforts, which are collectively referred to as the [[https:// | + | |
- | - **Training**: | + | |
- | - **Implementation**: | + | |
- | - **Rethinking Utility**: Clinical utility of making a prediction, and taking actions depends on factors beyond model accuracy, such as lead time offered by the prediction, the existence of a mitigating action, the cost and ease of intervening, | + | |
- | - **Safety, ethics, and health system effects**: We map the multiple groups involved in executing a prediction-action pair and study their varying perspectives, | + | |
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- | If done right, the adoption of efficacious prediction-action pairs can massively improve the ability of a health system to find patients at risk and act early. As part of this effort, we search for clinical situations where the application of risk-stratification and proactive action can provide cost-effective, | + | |
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