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SUMMARY:AI for Health with Wearables - Chenyang Lu\, Washington University
  in St Louis
DTSTART:20240213T160000Z
DTEND:20240213T170000Z
UID:TALK203656@talks.cam.ac.uk
CONTACT:Cecilia Mascolo
DESCRIPTION:Abstract: Artificial intelligence (AI) has emerged as a powerf
 ul tool for solving complex health problems using data-driven approaches. 
 AI for health is fueled by both the advancement in AI methods and the avai
 lability of data provided by electronic health records (EHR) and wearables
 . This talk will explore the potential to support precision medicine using
  wearables that enable unobtrusive monitoring of patients in their daily l
 ives. To harness the full potential of wearables\, it is crucial to develo
 p machine learning (ML) models to extract reliable clinical information fr
 om noisy and incomplete sensor data. Moreover\, these ML approaches need t
 o scale effectively across a wide range of sample sizes\, providing robust
  predictions even with limited data\, while enhancing predictive power wit
 h large datasets. We will highlight three clinical studies that use Fitbit
  wristbands as wearable instruments. First\, we have established a robust 
 feature engineering and ML pipeline specifically tailored for wearable stu
 dies with limited sample sizes. This pipeline demonstrated its effectivene
 ss in predicting post-operative complications in a prospective clinical tr
 ial of patients undergoing pancreatic surgery. Second\, we have developed 
 WearNet\, an end-to- end deep learning model designed to detect mental hea
 lth disorders using wearable data. WearNet has been trained and validated 
 on a large public dataset comprising 8\,996 participants\, including 1\,24
 7 diagnosed with mental disorders. Finally\, we have explored multi-task M
 L approaches to predict individualized responses to depression therapy bas
 ed on wearable data collected in a randomized controlled trial (RCT). By t
 he end of the talk\, we will discuss the opportunities and directions in t
 he interdisciplinary field of AI and wearables for health\, showcasing the
  transformative impact they can have on healthcare outcomes.\n\n\nBio: Che
 nyang Lu is the Fullgraf Professor of Computer Science & Engineering and h
 olds joint appointments as Professor of Anesthesiology and in Medicine at 
 Washington University in St. Louis. He is the founding director of the AI 
 for Health Institute (AIHealth)\, a multidisciplinary institute dedicated 
 to driving AI innovation in health research. His research interests includ
 e AI for health\, Internet of Things\, real-time systems\, and cyber-physi
 cal systems. In 2022\, he was honored with the Outstanding Technical Achie
 vement Award and Leadership Award from the IEEE Technical Community on Rea
 l-Time Systems (TCRTS). He has also been recognized by a Test of Time Awar
 d from ACM Conference on Embedded Networked Sensor Systems (SenSys)\, an I
 nfluential Paper Award from IEEE Real-Time and Embedded Technology and App
 lications Symposium (RTAS)\, and nine Best or Outstanding Paper Awards. He
  is Editor-in-Chief of ACM Transactions on Cyber-Physical Systems. He also
  served as Editor-in-Chief of ACM Transactions on Sensor Networks\, Chair 
 of TCRTS and chaired leading conferences on IoT\, real-time systems\, and 
 cyber-physical systems. He is a Fellow of ACM and IEEE.
LOCATION:Online
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