Looking forward to presenting our team's research on AI for EHR at The Big Data Institute at Oxford on July 10th at 2 pm! Thanks to Sumeeta and Prof @nichols.bsky.social for organising.

Link: talks.ox.ac.uk/talks/id/590...

This could not have transpired without the leadership of Prof Kazem Rahimi and team: Drs/Profs. Yikuan Li, Mo Mamouei, Milad Nazarzadeh, @rezakhorshidi.bsky.social, @gscollins.bsky.social, @vickersbiostats.bsky.social, Gosia Wamil, Chris Yau, Rod Jackson, & Goodarz Danaei!

🔗: tinyurl.com/LDHTRisk

🌍 Why it matters:
TRisk offers a scalable, equitable approach to prevention. More than just achieving strong predictive performance, TRisk can reduce over-treatment - crucial for efficient allocation of therapies - while identifying those most likely to benefit⚕️🫀🤖

📉 What this means for CVD prevention:
In the general population:
🩺 TRisk reduced treatment recommendations by 34% vs QRISK3, without increasing false negatives.

In diabetes:
🩺 24% fewer treatment recommendations w respect to "treat all" strategy, with minimal missed cases (0.2%).

⚙️ What we found:
For incident CVD prediction, TRisk showed:
✅ Higher discrimination (C-index 0.91) and net benefit than benchmark models
✅ Better performance across age, sex & socio-economic deprivation groups
✅ Less sensitivity to age ranges
✅ Excellent calibration

🧠 How we built it:
TRisk is a Transformer-based survival model trained on:
🔹 2.2M patient records for training
🔹 750K for validation
🔹 3.8k diagnoses, 390 meds, 1.4k tests for model input

Importantly, it uses raw, longitudinal EHR sequences (figure) - no manual variable selection and no imputation.

📚 Why now?
Current tools for CVD prediction like QRISK3 often over-recommend treatment—especially in diabetes, where everyone is treated regardless of risk.

TRisk changes that. It analyses full EHR histories to predict CVD risk more precisely, not just based on age or a fixed checklist.

Thanks @erictopol.bsky.social🙌 Kazem and I are excited to share our paper, now in press at The Lancet Digital Health! We introduce TRisk, a Transformer-based survival model for 10-year CVD risk prediction and more refined preventive therapy recommendations 🫀📊

A short 🧵...

Appreciate the shout-out @erictopol.bsky.social!