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Workshop: Machine Learning for Mobile Health

Joe Futoma, Walter Dempsey, Katherine Heller, Yi-An Ma, Nicholas Foti, Marianne Njifon, Kelly Zhang, Hera Shi

2020-12-12T07:00:00-08:00 - 2020-12-12T14:30:00-08:00
Abstract: Mobile health (mHealth) technologies have transformed the mode and quality of clinical research. Wearable sensors and mobile phones provide real-time data streams that support automated clinical decision making, allowing researchers and clinicians to provide ecological and in-the-moment support to individuals in need. Mobile health technologies are used across various health fields. Their inclusion in clinical care has aimed to improve HIV medication adherence, to increase activity, supplement counseling/pharmacotherapy in treatment for substance use, reinforce abstinence in addictions, and to support recovery from alcohol dependence. The development of mobile health technologies, however, has progressed at a faster pace than the science and methodology to evaluate their validity and efficacy.

Current mHealth technologies are limited in their ability to understand how adverse health behaviors develop, how to predict them, and how to encourage healthy behaviors. In order for mHealth to progress and have expanded impact, the field needs to facilitate collaboration among machine learning researchers, statisticians, mobile sensing researchers, human-computer interaction researchers, and clinicians. Techniques from multiple fields can be brought to bear on the substantive problems facing this interdisciplinary discipline: experimental design, causal inference, multi-modal complex data analytics, representation learning, reinforcement learning, deep learning, transfer learning, data visualization, and clinical integration.

This workshop will assemble researchers from the key areas in this interdisciplinary space necessary to better address the challenges currently facing the widespread use of mobile health technologies.


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2020-12-12T07:00:00-08:00 - 2020-12-12T07:10:00-08:00
2020-12-12T07:10:00-08:00 - 2020-12-12T07:30:00-08:00
Invited Talk: Matthew Nock
Matthew Nock
2020-12-12T07:30:00-08:00 - 2020-12-12T07:50:00-08:00
Invited Talk: Lee Hartsell
Lee Hartsell
2020-12-12T07:50:00-08:00 - 2020-12-12T08:10:00-08:00
Invited Talk: Ally Salim Jr
Ally Salim Jr
2020-12-12T08:15:00-08:00 - 2020-12-12T08:25:00-08:00
Towards Personal Hand Hygiene Detection in Free-living Using Wearable Devices
Qu Tang
2020-12-12T08:25:00-08:00 - 2020-12-12T08:35:00-08:00
Using Wearables for Influenza-Like Illness Detection: The importance of design
Bret Nestor
2020-12-12T08:35:00-08:00 - 2020-12-12T08:45:00-08:00
Representing and Denoising Wearable ECG Recordings
Jeffrey Chan
2020-12-12T08:45:00-08:00 - 2020-12-12T09:15:00-08:00
Discussion for Invited Speakers: Matthew Nock, Lee Hartsell, Ally Salim Jr
2020-12-12T09:15:00-08:00 - 2020-12-12T10:00:00-08:00
Poster Session in Gather Town
2020-12-12T10:00:00-08:00 - 2020-12-12T11:00:00-08:00
Lunch / Networking Break
2020-12-12T11:00:00-08:00 - 2020-12-12T11:20:00-08:00
Invited Talk: Susan Murphy
Susan Murphy
2020-12-12T11:20:00-08:00 - 2020-12-12T11:40:00-08:00
Invited Talk: Tanzeem Choudhury
Tanzeem Choudhury
2020-12-12T11:40:00-08:00 - 2020-12-12T12:00:00-08:00
Invited Talk: Tim Althoff
Tim Althoff
2020-12-12T12:00:00-08:00 - 2020-12-12T12:15:00-08:00
2020-12-12T12:15:00-08:00 - 2020-12-12T12:25:00-08:00
A generative, predictive model for menstrual cycle lengths that accounts for potential self-tracking artifacts in mobile health data
Kathy Li
2020-12-12T12:25:00-08:00 - 2020-12-12T12:35:00-08:00
Using Convolutional Variational Autoencoders to Predict Post-Trauma Health Outcomes from Actigraphy Data
Ayse Selin Cakmak
2020-12-12T12:35:00-08:00 - 2020-12-12T12:45:00-08:00
Fast Physical Activity Suggestions: Efficient Hyperparameter Learning in Mobile Health
Marianne Menictas
2020-12-12T12:45:00-08:00 - 2020-12-12T13:15:00-08:00
Discussion with Invited Speakers: Susan Murphy, Tanzeem Choudhury, Tim Althoff
2020-12-12T13:15:00-08:00 - 2020-12-12T14:15:00-08:00
Poster Session in Gather Town
2020-12-12T14:15:00-08:00 - 2020-12-12T14:30:00-08:00
Concluding Remarks