Chris Williams

Postdoc @UCSF_BCHSI Butte lab. MD alum @Cambridge_Uni. Previously AFP @CUH_NHS.

[Chris Williams @cykwilliams]

Such a pleasure to be live on the @abc7newsbayarea evening news discussing how AI might one day be used in #ER triage! Check out the replay here if you missed it (from 1.55): https://t.co/R389b2SPrR @UCSFHospitals @UCSF_DOCIT @atulbutte

[Chris Williams @cykwilliams]

Thrilled to announce our latest paper 'Physician- and Large Language Model–Generated Hospital Discharge Summaries', out today in @JAMAInternalMed!

[JAMA Internal Medicine @JAMAInternalMed]

LLM-generated discharge summaries were of comparable quality to those generated by physicians, though they contained more errors, and both types had low overall harmfulness scores.

https://t.co/uhSRZsrCVw

[Lisa Rotenstein MD @LisaRotenstein]

@cykwilliams presenting our results on use of GPT to find out why patients are not getting follow up colonoscopies after a positive FIT test
#quality #AI with @UrmimalaSarkar @j_r_a_m funded by The Doctors Company

@UCSF_DOCIT

[Cathy Gao-Howard, MD MS @CatGaoHow]

Standing room only and multiple hallway spillovers in these LLM talks! #AMIA2024 @AMIAinformatics with talks on #Gatortron, generating DC summaries @cykwilliams @UCSFHospitals, HTN NLP @JianchengYe, extracting #SDOH by Tim @IAIM_NU @yuanhypnosluo 🎉

[Chris Williams @cykwilliams]

Excited to be at #AMIA2024 in SF this week, giving two talks (both today!):
➡️ Evaluating Large Language Models for Drafting ED Discharge Summaries
➡️ Utilizing GPT-4 to determine reasons for missed follow-up colonoscopy following abnormal non-invasive colorectal cancer screening

[UCSF Health @UCSFHospitals]

#AI is helpful in an ER setting but shouldn't be blindly trusted, UCSF’s Dr. @cykwilliams tells @kron4news. It can help answer exam questions & draft notes—"but it’s not currently designed for situations that call for multiple considerations," he explains. https://t.co/plGZu3nQEr

[Chris Williams @cykwilliams]

Huge thanks to @bmeow19, @AaronKornblith and @atulbutte for their support on this!

[Chris Williams @cykwilliams]

Thrilled to announce our latest paper 'Evaluating the use of large language models to provide clinical recommendations in the Emergency Department' published today in Nature Communications!

https://t.co/1MmGIoD1t6

[Chris Williams @cykwilliams]

Excited to announce our latest paper "Enhancing emergency department charting: Using Generative Pre-trained Transformer-4 (GPT-4) to identify laceration repairs"!

Congrats to @karanbains and the rest of the team! @atulbutte @AaronKornblith

https://t.co/yXyum9xjng

[UCSF Bakar Computational Health Sciences Institute @UCSF_BCHSI]

UCSF's Town Hall this Friday, 7/12 will include Bakar postdoc @cykwilliams "How AI Can Help Emergency Department Prioritization" - new time at 12-1pm. Tune in! https://t.co/Lzha0DS7tu His recent work: https://t.co/0UEza1dTlf

[Chris Williams @cykwilliams]

Excited to announce our latest paper "Application of the Sepsis-3 criteria to describe sepsis epidemiology in the Amsterdam UMCdb intensive care dataset" published today! @tedinburgh_ @drPaulElbers @AriErcole

https://t.co/Jyph6fTblp

[Chris Williams @cykwilliams]

Thanks to @KCBSRadio for having me on air!

[UCSF Health @UCSFHospitals]

#AI can analyze and categorize a patient’s symptoms—possibly helping w/ future patient triage in the ER. Out of 2 patients, a study found the model can identify which condition was more serious 89% of the time, UCSF’s Christopher Williams says. 🔊 : https://t.co/qkT8QjANfs

[Atul Butte @atulbutte]

PhD exit talk by Brenda Miao @bmeow19 happening on Thursday 2pm @UCSF Byers Auditorium, with reception to follow! Join us in celebrating Brenda's PhD work!

Uncovering Strategies For Personalized Treatment Selection Using Large Language Models

Healthcare data has never been so accessible to patients and physicians, from smartphones and other remote monitoring devices to improved Electronic Medical Record (#EMR) data access. Despite this increasing ubiquity, insights from these data are often only captured in medical notes and other complex, spare, and unstructured real-world data. Here, we develop methods to use large language models (#LLM) to identify points of actionable insights from real-world data for both digital and pharmaceutical therapeutics. These new methods allow us to take an unprecedented look at the conversations, decisions, and medical expertise captured in millions of clinical notes and other real-world text data. #AI

[Chris Williams @cykwilliams]

Excited to be at @AMIAinformatics #CIC24 in Minneapolis this week alongside an incredible @UCSFHospitals @UCSF_DOCIT team, giving a talk on how #LLMs can be used to identify barriers to optimal patient care #qualityimprovement

Join us at 9.30 am CT Wednesday in Marquette 2&3!

[UCSF Health @UCSFHospitals]

#AI can help triage patients in emergency departments, a study in @JAMANetworkOpen finds. But lead author Dr. Christopher Williams cautions: “First we need to know if it works & understand how it works, & then be careful & deliberate in how it is applied." https://t.co/56wMUr0CAV

[Catherine Ho @Cat_Ho]

In one of the first studies to test whether AI can help triage real-world ER patients, new UCSF research suggests AI could one day help doctors make one of the most critical decisions in medicine: who to give urgent medical care to first https://t.co/I83Q6MlhvB via @sfchronicle

[M. Kit Delgado, MD, MS @kit_delgadoMD]

@EricTopol @JAMANetworkOpen @atulbutte We commend @cykwilliams @atulbutte and team on this new work. In this @JAMANetworkOpen editorial we offer some thoughts on the study's promising findings and important caveats for advancing this important area of work @AriBFriedman @garyweissman https://t.co/kPZlZkBiYD

[Chris Williams @cykwilliams]

Tune into @abc7newsbayarea live at 5.30 pm PT tonight where I'll be discussing our findings https://t.co/sdTqJumisW @atulbutte

[Chris Williams @cykwilliams]

Thrilled to announce our latest paper "Use of a Large Language Model to Assess Clinical Acuity of Adults in the Emergency Department" published today in @JAMANetworkOpen @TravisZack2 @bmeow19 @madhumitasushil Michelle Wang @AaronKornblith @atulbutte

[Atul Butte @atulbutte]

Out today in @JAMANetworkOpen! Cross-sectional study w/ 10 000 pairs of ED visits, @OpenAI GPT accurately identified the patient w/ higher acuity when given pairs of deidentified presenting histories. Work by @cykwilliams @TravisZack2 @bmeow19 @madhumitasushil Michelle Wang @AaronKornblith.

[Eric Topol @EricTopol]

The potential for LLM #AI to do accurate triage in the emergency department for patient acuity
@JAMANetworkOpen @atulbutte
https://t.co/y0YiOBXLB2