Motivation
The COVID-19 pandemic has illuminated the longstanding inequities and fractures within the healthcare system. As we build the future of healthcare, we can aim to create a system that is more fair, more tailored, and more cost-effective. Rapid advances in sequencing and genomic technologies as well as large data streams from electronic health records (EHRs), imaging data, and wearables have created new opportunities for reimagining healthcare delivery. With increasing amounts of multi-dimensional data from these modalities, we will require machine learning and other novel approaches to discover new insights and to ultimately improve healthcare delivery.
Source: National Cancer Institute
Session topics
Our session will focus on machine learning and other novel methods that leverage either genomics or other forms of multi-modal clinical data in order to improve healthcare. These improvements may range from identifying ways to risk stratify or treat patients for higher value care to creating tools for mitigating bias in health systems.
Broadly, we are interested in:
- Methods for analyzing ‘omics data to identify patients at higher risk of disease or who might benefit from particular targeted therapies
- Decision support tools that use multi-modal data to help streamline diagnosis or treatment
- Methods for integrating the most up to date literature guidelines into clinical practice
- Tools for analyzing multi-modal data such as lifestyle, environmental, geographic, and healthcare records to gain new insights for delivering better or tailored clinical care
- Methods for interpreting ‘omics data and/or incorporating these interpretations into the clinical care pipeline
- Methods for using ‘omic and lifestyle data to improve personalized diagnostics that take into account an individual’s genetic background and environmental factors
In this year’s session we are particularly interested in submissions that tackle inequities such as:
- Tools or methods that address bias in a clinical domain and aim to help correct that bias
- Tools or methods that detect bias in either large ‘omics or multi-modal datasets
- Methods/tools that address or reveal the potential for biases in machine learning in healthcare
- Methods for interpreting rare genetic variants, particularly in traditionally under-represented populations whose genetics may not be well represented by commonly used genetic datasets or risk scores
- Methods for analyzing population-specific genomic sequences that are not captured in the current reference human genome sequence
- Methods for delivering insights using ‘omics data on traditionally excluded and diverse patient groups
Session organizers
Submission Information
The submitted papers are fully reviewed and accepted on a competitive basis.
Important dates
- August 2, 2021: Call for papers deadline (no extensions will be granted)
- September 13, 2021: Notification of paper acceptance.
- October 1, 2021: Camera-ready final papers deadline.
- December 6, 2021: Poster abstract submission deadline.
- January 3-7, 2022: 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.
Last updated: April 5th, 2021