Geoff Tison

[Geoff Tison @GeoffTison]

Looking forward to Co-Chairing this NIH-NHLBI Workshop on Artificial Intelligence for Clinical Decision Support Sept 9-10, 2025 in Bethesda, MD.

All are welcome, join us in-person or virtually. Register here: https://t.co/74pGn3BtEf

[Pranav Rajpurkar @pranavrajpurkar]

We analyze performance for ECGs over 4 datasets: PTB-XL, Chapman-Shaoxing, Georgia 12-lead ECG Challenge, and CPSC. @GeoffTison

We show you how to visualize the normalized signal for each lead as well as train models with a 7-label task across datasets.

https://t.co/RcDnvusbuG

[Geoff Tison @GeoffTison]

This work shows how #AI can expand the utility of existing medical data and procedures to provide clinically-actionable insights and potentially decrease medical risks. @Jeffolgin, @BarriosEtAl, @Sean_abreau, @DerekSoMD, @Zeeshan_A2

[Geoff Tison @GeoffTison]

We’re excited to share CathEF in our latest @JAMACardio paper, an #AI algorithm that provides novel information about cardiac pumping function (LVEF) from standard coronary angiograms. https://t.co/IBK0SnAA2I. Read more also at https://t.co/JsFZpLQTTI @RobertAvramMD

[Geoff Tison @GeoffTison]

We then externally validated CathEF in a different country @UOHIResearch showing similarly strong performance. This is a technological advancement for angiography, using #AI to assess real-time LV systolic function from any routine angiogram without any added risk or procedures.

[Robert Avram @RobertAvramMD]

@GeoffTison @UCSFCardiology created an AI-powered algorithm that accurately predicts 💝myocardial injury using #ECG data.
✅The algorithm's negative predictive value of 80% allows it to triage low-risk patients using a simple and cost-effective ECG. https://t.co/5vVg8uK5cx #AI

[Atul Butte (In Memoriam) @atulbutte]

I am so proud to be part of an amazing community at @UCSF pushing the boundaries of biomedical #AI, including @UCSF_BCHSI @arnaoutlab @GeoffTison @sharmilamajumda @AaronNeinstein @madhumitasushil @UCSF_Ci2 and so many others!

[UCSF Bakar Computational Health Sciences Institute @UCSF_BCHSI]

UCSF Center for Real World Evidence Collab w/ @JanssenUS published in @JCardFail "Electrocardiogram Detection of Pulmonary Hypertension Using Deep Learning" https://t.co/DPl2mZqhKs @atulbutte @GeoffTison RWE, signal processing, AND machine learning / deep learning!

[𝐉𝐨𝐬𝐡 𝐁𝐚𝐫𝐫𝐢𝐨𝐬 @BarriosEtAl]

We present a new perspective in @cellrepmed on the present state and future outlook of AI and machine learning in cardiovascular medicine: https://t.co/0xFXtwlSFN @GeoffTison A thread:
#AI, #Cardiology

[UCSF Cardiology @UCSFCardiology]

A study published in @LancetGH by lead author @GeoffTison and @UCSF researchers shows that physical activity remains decreased worldwide 2 years since #COVID19 onset. https://t.co/cI3ieJsA3z

[JACC Journals @JACCJournals]

AI analysis of HCM ECGs correlates with longitudinal hemodynamic, cardiac structural and laboratory markers in obstructive HCM patients. https://t.co/2JuPKMMkSC

#JACC #cvHCM #ECG #EKG #CardioTwitter @GeoffTison @noseworthypeter

[Geoff Tison @GeoffTison]

Full text link https://t.co/XqWN3e5Ue1

[Geoff Tison @GeoffTison]

Out this week in #JACC, we show that AI analysis of ECGs not only diagnoses disease but can assess disease severity and response to drug treatment (tracking cardiac hemodynamics and BNP). @JACCJournals https://t.co/KJoZP6KMw2

[Geoff Tison @GeoffTison]

@bmsnews @UCSFHospitals @UCSFCardiology @ucsf_echo @ACCinTouch https://t.co/yjJCSyL0wq

[Allison Aubrey @AubreyNPR]

The pandemic winter is ending, so why are our pandemic habits sticking around?

I needed some #Inspiration so I reached out to some smart people for tips to reboot

https://t.co/O81nY0JjWS

@mchonig @katy_milkman @GeoffTison @gregorymmarcus @MorningEdition

[UCSF Health @UCSFHospitals]

Reduced physical activity & weight gain are changes many have experienced since the #pandemic, but it’s “not surprising,” Dr. @GeoffTison says. “People are just less used to being active." Learn about #GoalSetting and other tips to get back on track. https://t.co/31E9pqUkCl

[CCS @SCC_CCS]

☑️ November #CJC Editor's pick from @StanleyNattel Predicting Incident Heart Failure in Women With Machine Learning: The Women’s Health Initiative Cohort. Corresponding author: @GeoffTison

👉 https://t.co/ZqKxIR7Bme