Could AI Identify Alzheimer’s Risk Factors from Electronic Health Records?

With the recent surge in artificial intelligence and machine learning technology, one of the most exciting fields it could revolutionize is health care and, more specifically, the field of cognitive care and research. Dr. Marina Sirota and Alice Tang join the podcast to share their research on how AI could be used to predict one’s risk of developing Alzheimer’s disease based on their electronic health records. They also discuss what needs to be done to improve these algorithms and other ways this technology could be used in Alzheimer's disease research. Guests: Marina Sirota, PhD, associate professor, University of California San Francisco (UCSF), principal investigator, Sirota Lab, and Alice Tang, MD/PhD student, University of California San Francisco, postdoctoral fellow, Sirota Lab Show Notes Read Alice Tang and Dr. Sirota’s study, “Leveraging electronic health records and knowledge networks for Alzheimer’s disease prediction and sex-specific biological insights,” online through the journal Nature.. Learn more about Sirota Lab on their website. Learn more about Dr. Sirota on her UCSF profile. Connect with us Find transcripts and more at our website. Email Dementia Matters: [email protected] Follow us on Facebook and Twitter. Subscribe to the Wisconsin Alzheimer’s Disease Research Center’s e-newsletter. Enjoy Dementia Matters? Consider making a gift to the Dementia Matters fund through the UW Initiative to End Alzheimer’s. All donations go toward outreach and production.

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