All Work Published on Healthcare
Scholars develop a new model to surface high-risk messages and dramatically reduce the time it takes to reach a patient in crisis, from 10 hours to 10 minutes.
Scholars develop a new model to surface high-risk messages and dramatically reduce the time it takes to reach a patient in crisis, from 10 hours to 10 minutes.
Stanford researchers urge coordinated action by federal and state governments, academic institutions, and hospitals to avoid harms from the deployment of AI in biomedicine and clinical care.
Stanford researchers urge coordinated action by federal and state governments, academic institutions, and hospitals to avoid harms from the deployment of AI in biomedicine and clinical care.
Stanford Ethicists Developing Guidelines for the Safe Inclusion of Pediatric Data in AI-Driven Medical Research
AI algorithms often are trained on adult data, which can skew results when evaluating children. A new perspective piece lays out an approach for pediatric populations.
AI algorithms often are trained on adult data, which can skew results when evaluating children. A new perspective piece lays out an approach for pediatric populations.
Black and brown skin tones are underrepresented in books meant to teach doctors to recognize skin disease. The shortfall could contribute to racial disparities in diagnosis and treatment.
Black and brown skin tones are underrepresented in books meant to teach doctors to recognize skin disease. The shortfall could contribute to racial disparities in diagnosis and treatment.
AI Researchers Tap into Medical Twitter To Create Powerful New Analysis Tool
Stanford researchers discover a rich new data source in the anonymized pathology images and online comments of thousands of pathologists.
Stanford researchers discover a rich new data source in the anonymized pathology images and online comments of thousands of pathologists.
How the medical field can best harness LLMs, from evaluating the accuracy of algorithms to ensuring they fit with a provider's workflow.
How the medical field can best harness LLMs, from evaluating the accuracy of algorithms to ensuring they fit with a provider's workflow.