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Combining knowledge of clinical medicine and Artificial Intelligence | Emma Rocheteau
Manage episode 359452983 series 2859018
Emma is a final-year medical student at the University of Cambridge and also pursuing her Ph.D. in Machine Learning. With her knowledge of clinical decision-making, she is working on research projects that leverage machine-learning techniques to improve clinical workflow. She will be taking her role as an academic doctor post her graduation.
Time stamps of the conversation
00:00:00 Introduction
00:02:08 From clinical science to learning AI
00:13:15 Learning the basics of Artificial Intelligence
00:20:12 Promise of AI in medicine
00:30:13 Do we really need interpretable AI models for clinical decision-making?
00:38:47 Using AI for more clinically-useful problems
00:50:55 Facilitating interdisciplinary efforts
00:54:06 Predicting length of stay in ICUs using convolutional neural networks
01:03:04 AI for improving clinical workflows and biomarker discovery
01:07:55 Clustering disease trajectories in mechanically ventilated patients using machine learning
01:16:37 ChatGPT for medical research or clinical decision making
01:25:21 Quality over quantity of AI works published nowadays
01:31:07 Advice to researchers
Emma's Homepage: https://emmarocheteau.com/
LinkedIn: https://www.linkedin.com/in/emma-rocheteau-125384132/
Also check-out these talks on all available podcast platforms: https://jayshah.buzzsprout.com
About the Host:
Jay is a Ph.D. student at Arizona State University.
Linkedin: https://www.linkedin.com/in/shahjay22/
Twitter: https://twitter.com/jaygshah22
Homepage: https://www.public.asu.edu/~jgshah1/ for any queries.
Stay tuned for upcoming webinars!
***Disclaimer: The information contained in this video represents the views and opinions of the speaker and does not necessarily represent the views or opinions of any institution. It does not constitute an endorsement by any Institution or its affiliates of such video content.***
Checkout these Podcasts on YouTube: https://www.youtube.com/c/JayShahml
About the author: https://www.public.asu.edu/~jgshah1/
92 episodi
Manage episode 359452983 series 2859018
Emma is a final-year medical student at the University of Cambridge and also pursuing her Ph.D. in Machine Learning. With her knowledge of clinical decision-making, she is working on research projects that leverage machine-learning techniques to improve clinical workflow. She will be taking her role as an academic doctor post her graduation.
Time stamps of the conversation
00:00:00 Introduction
00:02:08 From clinical science to learning AI
00:13:15 Learning the basics of Artificial Intelligence
00:20:12 Promise of AI in medicine
00:30:13 Do we really need interpretable AI models for clinical decision-making?
00:38:47 Using AI for more clinically-useful problems
00:50:55 Facilitating interdisciplinary efforts
00:54:06 Predicting length of stay in ICUs using convolutional neural networks
01:03:04 AI for improving clinical workflows and biomarker discovery
01:07:55 Clustering disease trajectories in mechanically ventilated patients using machine learning
01:16:37 ChatGPT for medical research or clinical decision making
01:25:21 Quality over quantity of AI works published nowadays
01:31:07 Advice to researchers
Emma's Homepage: https://emmarocheteau.com/
LinkedIn: https://www.linkedin.com/in/emma-rocheteau-125384132/
Also check-out these talks on all available podcast platforms: https://jayshah.buzzsprout.com
About the Host:
Jay is a Ph.D. student at Arizona State University.
Linkedin: https://www.linkedin.com/in/shahjay22/
Twitter: https://twitter.com/jaygshah22
Homepage: https://www.public.asu.edu/~jgshah1/ for any queries.
Stay tuned for upcoming webinars!
***Disclaimer: The information contained in this video represents the views and opinions of the speaker and does not necessarily represent the views or opinions of any institution. It does not constitute an endorsement by any Institution or its affiliates of such video content.***
Checkout these Podcasts on YouTube: https://www.youtube.com/c/JayShahml
About the author: https://www.public.asu.edu/~jgshah1/
92 episodi
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