PSB 2023 Seminar

Digital health technology data in biocomputing:

Research efforts and considerations for expanding access

Motivation

Data from digital health technologies (DHT), including wearable sensors like Apple Watch, Whoop, Oura Ring and Fitbit, are increasingly being used in biomedical research. In an effort to expand and democratize academic research from wearable sensors and related digital health technologies, we solicit novel research results leveraging DHT, describing novel analytical methods, and issues related to diversity, equity, inclusion (DEI) of both the underlying research data sets and the community of researchers working in this area.

Session topics

This Session solicits research results leveraging digital health technologies, including wearable sensor data, describing novel analytical methods, and issues related to diversity, equity, inclusion (DEI) of both the underlying research data sets and the community of researchers working in this area. We particularly encourage submissions describing opportunities for expanding and democratizing academic research using data from wearable sensors and related digital health technologies. Some specific topics may include (but are not restricted to):

• Algorithms for anomaly detection and digital biomarkers
• Leveraging population data for personalized and precision models (e.g., transfer learning)
• Moving into real-time detection (online learning methods; reinforcement learning)
• Disease or condition-specific insights using DHTs
• Novel methods for feature identification
• Other related analysis of wearables and/or other digital health data

• Methods to address challenges related to current research using DHTs including:

• Small sample size
• Narrow health focus
• Narrow population focus
• Limited outcome assessments
• Data deluge (data footprints, compression, ETL (extract, transfer, load))

• Verification & Validation
• Improving Reporting and Data Publishing
• Bridging the Regulatory Gap and Moving to Clinical Implementation
• Improving access to data and tools (FAIR principles, databases, online communities)
• Standards, frameworks, and tool development
• Interoperability between multiple vendors (commercial and/or open source)
• Security & Privacy considerations

Submission information

The submitted papers are fully reviewed and accepted on a competitive basis.

Important dates

• August 1, 2022: Call for papers deadline (no extensions will be granted)
• September 9, 2022: Notification of paper acceptance.
• October 3, 2022: Camera-ready final papers deadline.
• December 5, 2022: Poster abstract submission deadline.
• January 3-7, 2023: Conference dates.

Paper Format and Submission Portal

Please see the PSB paper format template and instructions at http://psb.stanford.edu/psb-online/psb-submit.

Paper Submissions

Unlike the abstracts at most biology conferences, papers in the PSB proceedings are archival, rigorously peer-reviewed publications. PSB publications are Open Access and linked directly from MEDLINE/PubMed and Google Scholar for wide accessibility. They should be thought of as short journal articles that may be cited on CVs and grant reports.

Travel Fellowships for Trainees

PSB traditionally provides fellowships for select trainees. The application process opens upon paper acceptance. Individuals from underrepresented communities are particularly encouraged to participate in the conference and apply for travel support.

Poster Format and Submission Portal

Poster presenters will be provided with an easel and a poster board 32"W x 40"H (80x100cm). One poster from each paid participant is permitted. See the submission portal web site for the instructions regarding poster submissions.

Link to PSB website

Session organizers

Jessilyn Dunn, PhD

Assistant Professor | Big Ideas Lab

Department of Biomedical Engineering

Department of Biostatistics & Bioinformatics

Duke University

@DrJessilyn ; @Big_Ideas_Lab

Michelle Holko, PhD, PMP

Principal Architect & Scientist

Google Cloud, Global Public Sector

michelleholko@google.com @mholko

Chris Lunt

CTO, All of Us Research Program

National Institutes of Health

chris.lunt@nih.gov