Samer Alabed

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Samer Alabed

Samer Alabed

@smrabd

🫀Radiologist #whyCMR #yesCCT | Senior Research Fellow in #AI @sheffielduni | @BSCImaging Executive Committee

Sheffield, Uk Katılım Ekim 2011
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Samer Alabed
Samer Alabed@smrabd·
@EricTopol @LancetDigitalH @curtlanglotz Thanks for the shout out, Eric. This is part of our work through the Topol Digital Fellowship, focused on making medical imaging reports more accessible for patients. Good progress so far, with more to come.
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Samer Alabed
Samer Alabed@smrabd·
Ever tried reading your own CT or MRI scan report? Found it confusing? AI can rewrite it into plain language. In 38 studies, patients say it helps and clinicians say it’s accurate but ~1% had significant errors. The future of radiology communication? Out today @LancetDigitalH
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BSCI BSCCT
BSCI BSCCT@BSCImaging·
Calling all radiology and cardiology trainees. Don't miss out on joining the only imaging society that encompasses all of cardiac imaging. Join by filling out this form 👉🏼 members.bsci.org.uk/amember/signup?
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Journal of Cardiovascular CT
Journal of Cardiovascular CT@journalCCT·
Tremamunno et al show that ultra–high-resolution photon-counting CT (PCD-CT) detects more plaques but less stenosis than EID-CT, reclassifying >50% of patients to lower CAD-RADS. PCD-CT doesn’t just sharpen images—it changes interpretation. doi.org/10.1016/j.jcct…
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David Wu, MD, PhD
David Wu, MD, PhD@DavidWuMDPhD·
What's the best AI model for medical advice? Most evals focus on accuracy; we benchmarked harm First, do NOHARM: 100 real cases, 12k+ expert ratings Preprint: arxiv.org/abs/2512.01241 Interactive leaderboard: bench.arise-ai.org
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Vishnu Ravi, MD
Vishnu Ravi, MD@vishnuravi·
Proud to share First Do NOHARM, the first medical AI benchmark created and named in the spirit of medicine's foundational principle. 2/3 of US clinicians and millions of patients use AI every day. But how often does AI advice actually harm patients? We built NOHARM to find out. Using 100 real clinical cases across 10 specialties, with 12,747 expert annotations, we measured harm frequency and severity from 31 LLMs. What we found: - Severe harm occurs in up to 1 of 5 of cases - 77% of serious errors are sins of omission, failing to recommend critical actions - Existing AI benchmarks poorly predict clinical safety - Multi-agent systems can substantially reduce harm - The best models outperform human generalist physicians on safety The uncomfortable truth: models tuned for caution can paradoxically increase harm by missing essential recommendations. And doing nothing is worse than every AI we tested. As AI moves from documentation to clinical decisions, we need explicit safety measurement, not just accuracy scores. Honored to have been part of this groundbreaking work by our ARiSE Healthcare Network team at @StanfordMed and @harvardmed, which is just the beginning, as we develop a full suite of realistic clinical benchmarks we are calling MAST: Medical AI Superintelligence Test that medical AI developers can use to evaluate the real-world clinical performance and safety of their own models. Reach out if you are interested in testing your model! I particularly enjoyed building this beautiful interactive leaderboard with @DavidWuMDPhD, Ethan Goh, Joel Koh, Emily Tat, Augustine Chemparathy, Adi Badhwar and Kanav Chopra, which you can use to explore our results, comparing solo models as well as multi-agent teams across many harm and safety metrics. Deeply grateful to @jonc101x for his mentorship and for making this work possible. Leaderboard and paper: bench.arise-ai.org
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BSCI BSCCT
BSCI BSCCT@BSCImaging·
Next online webinar Tuesday, 25th Nov 2025 between 6 p.m - 7 p.m Title: Imaging cardiac implantable electronic devices and associated complications with Xray and CT Speaker: Dr Giulia Benedetti, Consultant Cardiothoracic Radiologist, Guy's and St Thomas' NHS Foundation Trust
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Declan O'Regan
Declan O'Regan@DrDeclanORegan·
Three year fully funded fellowship for those in the "Transition to Independence" stage of their clinician scientist career. Either side of CCT date. We'll give you the support you need for a competitive fellowship in cardiovascular imaging / AI. #whyCMR lms.mrc.ac.uk/work/vacancies…
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The Royal College of Radiologists
The Royal College of Radiologists@RCRadiologists·
Exciting news 🎉 Bookings are now open for the return of the #RCRGlobalAI conference on 29-30 June 2026! Join us as we focus on safe and practical AI implementation in healthcare. Register at super early bird rates and help us shape what comes next: tinyurl.com/5yehe7xp
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Erica Tirr
Erica Tirr@erica_tirr·
📣 📣 Exciting opportunity to join the amazing Radiology team at Royal Papworth Hospital in Cambridge 🤩 For multimodality imaging in thoracic oncology, ILD, TAVI, ACHD, valve, pulmonary HTN, cardiomyopathy, transplant & critical care. Apply now! ⬇️ bit.ly/3T8Srbi
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Roberta Catania
Roberta Catania@Robi_Catania·
Listen to our next InAMinute series about an article recently published in @RadiologyCTI on Cardiac MRI reference ranges for cardiovascular function during exercise.
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Patricia Rodriguez-Lozano MD, MS 🇵🇪🫀
Proud to chair SCCT’s First Committee and excited to share our latest review: “CT‑derived Fractional Flow Reserve: Part 2 – Critical Appraisal of the Literature”, featuring insights from @FiRSTSCCT Huge thanks to the SCCT community & authors for their expertise! @AnamWaheed05 @Sot_Evangelou @Nidhi_Madan9 @ToddVillinesMD @FiRSTSCCT @Heart_SCCT sciencedirect.com/science/articl… @UvaDOM @UVACardsFellows @CardioUva
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BSCMR
BSCMR@BSCMR·
Don’t miss our next webinar ………Cardio-oncology………. which takes place in July‼️ Details below. 👀 Free registration for all @bscmr members is now open using the link below. ⬇️ tinyurl.com/2a2act5p
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