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R25 VOICE Section 1 - General Machine Learning in Medicine/ Imaging Papers
In this podcast, we discuss important themes from 3 papers and answer student generated questions. The papers we review are:
Chen, Jonathan H., and Steven M. Asch. 2017. “Machine Learning and Prediction in Medicine — Beyond the Peak of Inflated Expectations.” The New England Journal of Medicine 376 (26):2507–9.
Erickson, Bradley J., Panagiotis Korfiatis, Zeynettin Akkus, and Timothy L. Kline. 2017. “Machine Learning for Medical Imaging.” Radiographics: A Review Publication of the Radiological Society of North America, Inc 37 (2):505–15.
Obermeyer, Ziad, and Ezekiel J. Emanuel. 2016. “Predicting the Future — Big Data, Machine Learning, and Clinical Medicine.” The New England Journal of Medicine 375 (13):1216–19.
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By Yin AphinyanaphongsIn this podcast, we discuss important themes from 3 papers and answer student generated questions. The papers we review are:
Chen, Jonathan H., and Steven M. Asch. 2017. “Machine Learning and Prediction in Medicine — Beyond the Peak of Inflated Expectations.” The New England Journal of Medicine 376 (26):2507–9.
Erickson, Bradley J., Panagiotis Korfiatis, Zeynettin Akkus, and Timothy L. Kline. 2017. “Machine Learning for Medical Imaging.” Radiographics: A Review Publication of the Radiological Society of North America, Inc 37 (2):505–15.
Obermeyer, Ziad, and Ezekiel J. Emanuel. 2016. “Predicting the Future — Big Data, Machine Learning, and Clinical Medicine.” The New England Journal of Medicine 375 (13):1216–19.