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Though indeed, that prescription may well be under your name in the prescription drug monitoring program and used in the algorithm assigning you an overdose risk score! So double thanks for nothing (and sending her/him get well wishes).

Insurance denials, hospitals prescriptions, fraud detection—algorithm driven but rarely tested for accuracy or unintended side effects.

I can’t think of a group more desperately in need of hearing Kate Nicholson Kate is a sterling clear voice for the perspective of people with pain, whose survival & safety has been- in every way- an afterthought for most people at every #RxSummit

My op-ed for @LATimes with @LeoBeltsky on the devastating impact of DEA HQ proposed teleprescribing rules. latimes.com/opinion/story/…

Excited and proud to start new role as ED of UC Joint Computational Precision Health Program , groundbreaking program of UCSF and UC Berkeley working at the intersection of machine learning, computation, clinical/public health practice and equity. Brilliant colleagues and important work ahead.

High school students from underserved communities rocking it on AI and health. Talk about Next Generation evidence.

Unlocking the mysteries of the autonomic nervous system--pain while unconscious, interactions between mind and gut, and much more. Sandya Subramanian to bring her cutting-edge work to @UCjointCPH, UC Berkeley CDSS, UCSF Bakar Computational Health Sciences Institute and others in the field in 2024.

So right, and so we’ll deserved!

Algorithmic injustice: UnitedHealth used machine learning to push Medicare patients off rehab services--despite claims that algorithms were meant to guide, rather than dictate, decisions. Via .STAT by Casey Ross and colleagues.

Inspiring, bold project to bring the ethos of open science, shareable code, and brilliant clinicians, computer scientists, and patient advocates to transform use and impact of health data. Proud to be part. UC Joint Computational Precision Health Program Ida Sim @ucbids The Commons Project Foundation 2i2c UC Berkeley CDSS

Scandalous and routine. A symptom of system thinking obscuring humanity and common sense.

Returning to "X" after an absence, and with good news that my UC Joint Computational Precision Health Program program colleague @IdaSim recognized by @STATnews as one of 50 most shaping health science. Work on democratizing data for diabetes management--with The Commons Project Foundation--called out! buff.ly/3IgaBT6

So long as metrics for OUD (itself a fuzzy, poorly defined category) depend on structural factors that are themselves unstable (using as prescribed when the docs change their practices, getting in trouble with the law when the laws and enforcement are variable), it’s all a mess.

How can open collaboration accelerate AI research? 🤝 Join us at #FtCSF on Mar 15-16 to hear from Daniel Wolfe from UC Joint Computational Precision Health Program, on fostering partnerships between academia and industry to drive innovation. 👉 Sign up: lu.ma/ftc-sf-2025

Learning much on models to return value to data contributors, decentralized autonomous orgs and more. Funding The Commons —thank you. Conference a great forum held in a great space Internet Archive here in S.F. and good to discuss work of UC Joint Computational Precision Health Program in the company.

Bad training data in, bad generative AI out. Retraining Gemini beyond me—though maybe a fine tuned smaller LLM /RAG for drug use. And still want g to train model to recognize patterns for real-time drug checking purposes!

.Irene Chen on combining data sources to ensure that AI models work fairly and well in all settings and for all patients—and also on a new work examining what patients want from LLMs and how they want the health system to use them. @ucsf AI research day. Berkeley Computing, Data Science, and Society

CPH’s Adam Yala presenting on amazing work at UCSF AI research day with Maggie Chung and co using AI model to deliver same day mammogram results and follow up to patients at highest risk of breast cancer at safety-net hospital. #AI4H #breastcancer UCSF DoC-IT

CPH student Zhongyuan Liang explains his work, done with Irene Chen and colleagues, on using LLMs to extract data on treatment adherence from medical notes -and the perils of failing to include this kind of data in analysis of treatment efficacy. @ahli_cc chilconference