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Wisconsin Alzheimer‘s Disease Research Center에서 제공하는 콘텐츠입니다. 에피소드, 그래픽, 팟캐스트 설명을 포함한 모든 팟캐스트 콘텐츠는 Wisconsin Alzheimer‘s Disease Research Center 또는 해당 팟캐스트 플랫폼 파트너가 직접 업로드하고 제공합니다. 누군가가 귀하의 허락 없이 귀하의 저작물을 사용하고 있다고 생각되는 경우 여기에 설명된 절차를 따르실 수 있습니다 https://ko.player.fm/legal.
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Could AI Identify Alzheimer’s Risk Factors from Electronic Health Records?

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Manage episode 454817708 series 2925702
Wisconsin Alzheimer‘s Disease Research Center에서 제공하는 콘텐츠입니다. 에피소드, 그래픽, 팟캐스트 설명을 포함한 모든 팟캐스트 콘텐츠는 Wisconsin Alzheimer‘s Disease Research Center 또는 해당 팟캐스트 플랫폼 파트너가 직접 업로드하고 제공합니다. 누군가가 귀하의 허락 없이 귀하의 저작물을 사용하고 있다고 생각되는 경우 여기에 설명된 절차를 따르실 수 있습니다 https://ko.player.fm/legal.

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: dementiamatters@medicine.wisc.edu

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.

  continue reading

100 에피소드

Artwork
icon공유
 
Manage episode 454817708 series 2925702
Wisconsin Alzheimer‘s Disease Research Center에서 제공하는 콘텐츠입니다. 에피소드, 그래픽, 팟캐스트 설명을 포함한 모든 팟캐스트 콘텐츠는 Wisconsin Alzheimer‘s Disease Research Center 또는 해당 팟캐스트 플랫폼 파트너가 직접 업로드하고 제공합니다. 누군가가 귀하의 허락 없이 귀하의 저작물을 사용하고 있다고 생각되는 경우 여기에 설명된 절차를 따르실 수 있습니다 https://ko.player.fm/legal.

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: dementiamatters@medicine.wisc.edu

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.

  continue reading

100 에피소드

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