This year’s session will solicit research papers related to methodology development and applications of precision medicine and machine learning with a focus on approaches to improve healthcare.
‘Omics data have already begun to lay the groundwork for stratifying patients according to their individual risk and identifying targeted therapies. For example, the Clinical Pharmacogenetics Implementation Consortium (CPIC) has written guidelines for the clinical use of genetic variants for dosing drugs and avoiding adverse events. However, most of the research done in genomics has been in European ancestry populations; equitable precision medicine will require the inclusion of diverse populations.
Rich medical datasets allow the creation of tools that can help streamline care and provide decision support. Many of these tools leverage machine learning and deep learning techniques to streamline processes or provide decision support. We are interested in research looking at the full stack from “bytes” to “bedside” – papers on data-centric artificial intelligence, novel methodologies or unique applications of previously developed methods, and clinical implementation of machine learning tools.
Author: Andrew Coelho
We are interested in research looking at the full stack from “bytes” to “bedside” – papers on data-centric artificial intelligence, novel methodologies and unique applications of previously developed methods, and clinical implementation of machine learning tools.
The above are just a few of the ways healthcare can be improved from knowledge gained from large-scale ‘omics and multi-modal medical datasets.
Broadly, we are interested in:
Steven E. Brenner
University of California, Berkeley
Jonathan H. Chen
Stanford School of Medicine
Dana C. Crawford
Case Western Reserve University
Stanford School of Medicine University
Stanford University & Clario
Smidt Heart Institute, Cedars-Sinai Medical Center
Michelle Whirl-Carrillo, email@example.com.
The submitted papers are fully reviewed and accepted on a competitive basis.
Please see the PSB paper format template and instructions at http://psb.stanford.edu/psb-online/psb-submit.
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.
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 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 4th, 2022