Alone in the Ring (a research-based theatre production about inclusive healthcare workplaces) is coming to campus during the Annual Stanford School of Medicine Diversity Week and National Disability Employment Awareness Month, SMAC and Stanford Medicine and the Muse hope to continue the discussion on how to spark and sustain change towards inclusive workspaces. Alone in the Ring is followed by a discussion between the team and audience members. During the presentation, audience members are encouraged to reflect: How inclusive is your workspace? How could you make it more accessible?
CME Grand Rounds – Topic: TBD
Jocelyn D. Chertoff, MD, MS
Professor
Radiology, Obstetrics & Gynecology
Chair, Radiology
Dartmouth Hitchcock Medical Center
Join from PC, Mac, Linux, iOS or Android: https://stanford.zoom.us/j/600003703?pwd=RjcwS2MvOG1qVkxyL3U0RmNtUDVWdz09
Meeting ID: 600 003 703
Password: 566048
Or iPhone one-tap (US Toll): +18333021536,,600003703# or +16507249799,,600003703#
Or Telephone:
Dial: +1 650 724 9799 (US, Canada, Caribbean Toll) or +1 833 302 1536 (US, Canada, Caribbean Toll Free)
International numbers available: https://stanford.zoom.us/u/acuqphnvqT
ABSTRACT
Coming soon!
BIO
Coming soon!
Office of Faculty Development and Diversity and SMAC.
The OFDD team welcomes all Stanford community members to join our inaugural Health Equity Action Leadership (HEAL Network) event, Health Equity Research in the Latinx Community, where faculty who do this work will share their experiences in a fireside chat panel.
Moderator: Lisa Goldman-Rosas
Speakers: Dr. Ken Sutha, Dr. Peter Poullos, Dr. Holly Tabor
CME Grand Rounds Etta K. Moskowitz Lectureship – Topic: TBD
Elizabeth Krupinski, PhD
Professor & Vice Chair for Research
Radiology & Imaging Sciences
Emory University School of Medicine
Join from PC, Mac, Linux, iOS or Android: https://stanford.zoom.us/j/600003703?pwd=RjcwS2MvOG1qVkxyL3U0RmNtUDVWdz09
Meeting ID: 600 003 703
Password: 566048
Or iPhone one-tap (US Toll): +18333021536,,600003703# or +16507249799,,600003703#
Or Telephone:
Dial: +1 650 724 9799 (US, Canada, Caribbean Toll) or +1 833 302 1536 (US, Canada, Caribbean Toll Free)
International numbers available: https://stanford.zoom.us/u/acuqphnvqT
ABSTRACT
Coming soon!
BIO
Coming soon!
CME Grand Rounds – “Promote Your Academic Career Using Social Media”
Michael Gisondi, MD
Associate Professor & Vice Chair of Education
Emergency Medicine
Stanford University
Join from PC, Mac, Linux, iOS or Android: https://stanford.zoom.us/j/600003703?pwd=RjcwS2MvOG1qVkxyL3U0RmNtUDVWdz09
Meeting ID: 600 003 703
Password: 566048
Or iPhone one-tap (US Toll): +18333021536,,600003703# or +16507249799,,600003703#
Or Telephone:
Dial: +1 650 724 9799 (US, Canada, Caribbean Toll) or +1 833 302 1536 (US, Canada, Caribbean Toll Free)
International numbers available: https://stanford.zoom.us/u/acuqphnvqT
ABSTRACT
Coming soon!
BIO
Coming soon!
Roxana Daneshjou, MD, PhD
Assistant Professor, Biomedical Data Science & Dermatology
Assistant Director, Center of Excellence for Precision Heath & Pharmacogenomics
Director of Informatics, Stanford Skin Innovation and Interventional Research Group
Stanford University
Title: Building Fair and Trustworthy AI for Healthcare
Abstract: AI for healthcare has the potential to revolutionize how we practice medicine. However, to do this in a fair and trustworthy manner requires special attention to how AI models work and their potential biases. In this talk, I will cover the considerations for building AI systems that improve healthcare.
Mildred Cho, PhD
Professor of Pediatrics, Center of Biomedical Ethics
Professor of Medicine, Primary Care and Population Health
Stanford University
Title: Facilitating Patient and Clinician Value Considerations into AI for Precision Medicine
Abstract:
For the development of ethical machine learning (ML) for precision medicine, it is essential to understand how values play into the decision-making process of developers. We conducted five group design exercises with four developer participants each (N=20) who were asked to discuss and record their design considerations in a series of three hypothetical scenarios involving the design of a tool to predict progression to diabetes. In each group, the scenario was first presented as a research project, then as development of a clinical tool for a health care system, and finally as development of a clinical tool for their own health care system. Throughout, developers documented their process considerations using a virtual collaborative whiteboard platform. Our results suggest that developers more often considered client or user perspectives after changing the context of the scenario from research to a tool for a large healthcare setting. Furthermore, developers were more likely to express concerns arising from the patient perspective and societal and ethical issues such as protection of privacy after imagining themselves as patients in the health care system. Qualitative and quantitative data analysis also revealed that developers made reflective/reflexive statements more often in the third round of the design activity (44 times) than in the first (2) or second (6) rounds. These statements included statements on how the activity connected to their real-life work, what they could take away from the exercises and integrate into actual practice, and commentary on being patients within a health care system using AI. These findings suggest that ML developers can be encouraged to link the consequences of their actions to design choices by encouraging “empathy work” that directs them to take perspectives of specific stakeholder groups. This research could inform the creation of educational resources and exercises for developers to better align daily practices with stakeholder values and ethical ML design.