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Personalized medicine with AI

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Manage episode 387460828 series 1993932
Sisällön tarjoaa AI-Podden with Ather Gattami and Ather Gattami. AI-Podden with Ather Gattami and Ather Gattami tai sen podcast-alustan kumppani lataa ja toimittaa kaiken podcast-sisällön, mukaan lukien jaksot, grafiikat ja podcast-kuvaukset. Jos uskot jonkun käyttävän tekijänoikeudella suojattua teostasi ilman lupaasi, voit seurata tässä https://fi.player.fm/legal kuvattua prosessia.

Mika Gustafsson, Prof., and David Martinez, PhD student, both at Linköping University conduct research in Bioinformatics and precision medicine. They are exploring how to use complex patient data, both clinical and environmental (such as the lifestyle) to develop personalized treatments and to help understand diseases more in depth in order to take preventive measures. David and Mika explain why bioinformatics and precision medicine is so complex, given the number of parameters affecting the human body and their complex interplay. The challenge of data acquisition is another challenge. For that challenge, they are working on federated learning to train AI systems without requiring private data to be shared. Ather, Mika, and David discuss the trade-offs of using federated learning, and the performance degradation that one might get for not sharing the data to a central unit directly. David and Mika go on and tell us about the greatest impacts of AI on medicine in the near future, from personalized medicine to helping less wealthy countries.

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Personalized medicine with AI

AI-podden

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iconJaa
 
Manage episode 387460828 series 1993932
Sisällön tarjoaa AI-Podden with Ather Gattami and Ather Gattami. AI-Podden with Ather Gattami and Ather Gattami tai sen podcast-alustan kumppani lataa ja toimittaa kaiken podcast-sisällön, mukaan lukien jaksot, grafiikat ja podcast-kuvaukset. Jos uskot jonkun käyttävän tekijänoikeudella suojattua teostasi ilman lupaasi, voit seurata tässä https://fi.player.fm/legal kuvattua prosessia.

Mika Gustafsson, Prof., and David Martinez, PhD student, both at Linköping University conduct research in Bioinformatics and precision medicine. They are exploring how to use complex patient data, both clinical and environmental (such as the lifestyle) to develop personalized treatments and to help understand diseases more in depth in order to take preventive measures. David and Mika explain why bioinformatics and precision medicine is so complex, given the number of parameters affecting the human body and their complex interplay. The challenge of data acquisition is another challenge. For that challenge, they are working on federated learning to train AI systems without requiring private data to be shared. Ather, Mika, and David discuss the trade-offs of using federated learning, and the performance degradation that one might get for not sharing the data to a central unit directly. David and Mika go on and tell us about the greatest impacts of AI on medicine in the near future, from personalized medicine to helping less wealthy countries.

Don't forget to subscribe and follow us on Linkedin.

  continue reading

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