The joint UC Berkeley-UCSF Program in Computational Precision Health (CPH) will bridge medicine, statistics, and computation to improve the quality, efficiency, and equity of medicine and population health. BIDS Faculty Affiliate Maya Petersen is a CPH Co-Director, and CPH Core and Affiliate Faculty include BIDS Faculty Affiliates David Bamman, Joshua Blumenstock, and Bin Yu.
BIDS Health and Life Sciences Lead Maryam Vareth offers this project (#2) through UC Berkeley's Undergraduate Research Apprentice Program (URAP).
Research access to electronic health record (EHR) data is limited due to patient privacy concerns. Creating synthetic EHR data (data that models realistic patterns and yet does not correspond to real patient records) provides a potential mechanism to expand data access.
BIDS Health and Life Sciences Lead Maryam Vareth offers this project (#4) through UC Berkeley's Undergraduate Research Apprentice Program (URAP).
The CRIC Cervix Collection is a searchable image database — currently with 400 images (1,376 × 1,020 pixels) curated from conventional Pap smears, with manual classification of 11,534 cells — that makes digital cell image collections available for reproducible research and FAIR machine learning, with the potential to advance current efforts in training and testing machine learning algorithms for the automation of tasks as part of the cytopathological analysis in the routine work of laboratories.
BIDS Faculty Affiliate Maya Petersen is part of this collaboration of healthcare providers, infectious disease experts, community mobilizers, and people who are helping vulnerable populations through COVID-19.
COVID-19 disproportionately effects communities of color across the nation. In San Francisco, LatinX members make up roughly 50% of COVID-19 cases, despite being 15% of the population due to longstanding health inequities. Low-barrier access to testing and care are instrumental in curbing the pandemic.
The BIDS-BCHSI Research Xchange Forum was launched in October 2020 as an open discussion platform for the interdisciplinary exchange of ideas and research projects at the intersection of healthcare and data science, enabling participants to support the development, and research of the group's members, and to foster new collaborations.
