RT @chrisck: New paper published! 🎉 What are the challenges of translating exciting AI research in healthcare to real world clinical impact…
RT @ivanbeckley: What a stunning paper!! @chrisck and @alan_karthi are world class experts in translating AI for healthcare. Previledged to…
RT @MattFenech83: Great paper by @chrisck, @alan_karthi, @Dominic1King & team at Google Health/@DeepMindAI outlining how difficult it is to…
RT @chrisck: New paper published! 🎉 What are the challenges of translating exciting AI research in healthcare to real world clinical impact…
Great paper by @chrisck, @alan_karthi, @Dominic1King & team at Google Health/@DeepMindAI outlining how difficult it is to translate #AI 'bench' to bedside. Covers everything from technical, regulatory, & very importantly the sociocultural challenge
RT @chrisck: New paper published! 🎉 What are the challenges of translating exciting AI research in healthcare to real world clinical impact…
RT @quantrad: Interesting Google Health perspective on implementing medical AI. @AcrDsi @SIIM_tweets Key challenges for delivering clinical…
Interesting Google Health perspective on implementing medical AI. @AcrDsi @SIIM_tweets Key challenges for delivering clinical impact with artificial intelligence | BMC Medicine | Full Text https://t.co/cc3hTx0fua
What a stunning paper!! @chrisck and @alan_karthi are world class experts in translating AI for healthcare. Previledged to have learnt these insights from them first hand. Must must read!!!!
RT @chrisck: New paper published! 🎉 What are the challenges of translating exciting AI research in healthcare to real world clinical impact…
RT @alan_karthi: The “AI chasm” in healthcare: how will we cross over from today’s starting point (retrospective studies, offline diagnosti…
RT @chrisck: New paper published! 🎉 What are the challenges of translating exciting AI research in healthcare to real world clinical impact…
RT @wi_john: “Key challenges for the translation of AI systems in healthcare include those intrinsic to the science of machine learning, lo…
RT @chrisck: New paper published! 🎉 What are the challenges of translating exciting AI research in healthcare to real world clinical impact…
RT @Dominic1King: In this article with Google Health colleagues (led by @chrisck) we explore the important challenges in translating exciti…
RT @chrisck: New paper published! 🎉 What are the challenges of translating exciting AI research in healthcare to real world clinical impact…
RT @Vilavaite: Key challenges for delivering clinical impact with #AI: ✅Robust clinical evaluation, using metrics including quality of care…
RT @chrisck: New paper published! 🎉 What are the challenges of translating exciting AI research in healthcare to real world clinical impact…
“Key challenges for the translation of AI systems in healthcare include those intrinsic to the science of machine learning, logistical difficulties in implementation, and consideration of the barriers to adoption as well as of the necessary sociocultural o
RT @chrisck: New paper published! 🎉 What are the challenges of translating exciting AI research in healthcare to real world clinical impact…
RT @chrisck: New paper published! 🎉 What are the challenges of translating exciting AI research in healthcare to real world clinical impact…
RT @chrisck: New paper published! 🎉 What are the challenges of translating exciting AI research in healthcare to real world clinical impact…
RT @chrisck: New paper published! 🎉 What are the challenges of translating exciting AI research in healthcare to real world clinical impact…
RT @chrisck: New paper published! 🎉 What are the challenges of translating exciting AI research in healthcare to real world clinical impact…
RT @Dominic1King: In this article with Google Health colleagues (led by @chrisck) we explore the important challenges in translating exciti…
RT @chrisck: New paper published! 🎉 What are the challenges of translating exciting AI research in healthcare to real world clinical impact…
RT @alan_karthi: The “AI chasm” in healthcare: how will we cross over from today’s starting point (retrospective studies, offline diagnosti…
RT @chrisck: New paper published! 🎉 What are the challenges of translating exciting AI research in healthcare to real world clinical impact…
RT @Vilavaite: Key challenges for delivering clinical impact with #AI: ✅Robust clinical evaluation, using metrics including quality of care…
RT @chrisck: New paper published! 🎉 What are the challenges of translating exciting AI research in healthcare to real world clinical impact…
RT @pearsekeane: Great work Chris! It’s reassuring to see that people at the coal face in implementing clinical #AI (ie you!) are really en…
RT @chrisck: New paper published! 🎉 What are the challenges of translating exciting AI research in healthcare to real world clinical impact…
RT @chrisck: New paper published! 🎉 What are the challenges of translating exciting AI research in healthcare to real world clinical impact…
RT @alan_karthi: The “AI chasm” in healthcare: how will we cross over from today’s starting point (retrospective studies, offline diagnosti…
RT @pearsekeane: Great work Chris! It’s reassuring to see that people at the coal face in implementing clinical #AI (ie you!) are really en…
RT @alan_karthi: The “AI chasm” in healthcare: how will we cross over from today’s starting point (retrospective studies, offline diagnosti…
Key challenges for delivering clinical impact with #AI: ✅Robust clinical evaluation, using metrics including quality of care and patient outcomes ✅Identify algorithmic bias and unfairness Reduce brittleness ✅Improve generalisability and interpretability ht
RT @chrisck: New paper published! 🎉 What are the challenges of translating exciting AI research in healthcare to real world clinical impact…
RT @alan_karthi: The “AI chasm” in healthcare: how will we cross over from today’s starting point (retrospective studies, offline diagnosti…
RT @chrisck: New paper published! 🎉 What are the challenges of translating exciting AI research in healthcare to real world clinical impact…
RT @alan_karthi: The “AI chasm” in healthcare: how will we cross over from today’s starting point (retrospective studies, offline diagnosti…
The “AI chasm” in healthcare: how will we cross over from today’s starting point (retrospective studies, offline diagnostic accuracy) to the true end-goal (prospective evidence, real clinical benefit)? My colleague @chrisck sets out some of the key issues
'Developers of AI algorithms must be vigilant to potential dangers, including dataset shift, accidental fitting of confounders, unintended discriminatory bias, challenges of generalisation to new populations & unintended negative consequences of new al
RT @Dominic1King: In this article with Google Health colleagues (led by @chrisck) we explore the important challenges in translating exciti…
RT @Dominic1King: In this article with Google Health colleagues (led by @chrisck) we explore the important challenges in translating exciti…
RT @chrisck: New paper published! 🎉 What are the challenges of translating exciting AI research in healthcare to real world clinical impact…
RT @chrisck: New paper published! 🎉 What are the challenges of translating exciting AI research in healthcare to real world clinical impact…
RT @chrisck: New paper published! 🎉 What are the challenges of translating exciting AI research in healthcare to real world clinical impact…
RT @chrisck: New paper published! 🎉 What are the challenges of translating exciting AI research in healthcare to real world clinical impact…
RT @chrisck: New paper published! 🎉 What are the challenges of translating exciting AI research in healthcare to real world clinical impact…
RT @chrisck: New paper published! 🎉 What are the challenges of translating exciting AI research in healthcare to real world clinical impact…
RT @chrisck: New paper published! 🎉 What are the challenges of translating exciting AI research in healthcare to real world clinical impact…
RT @Dominic1King: In this article with Google Health colleagues (led by @chrisck) we explore the important challenges in translating exciti…
RT @chrisck: New paper published! 🎉 What are the challenges of translating exciting AI research in healthcare to real world clinical impact…
RT @chrisck: New paper published! 🎉 What are the challenges of translating exciting AI research in healthcare to real world clinical impact…
RT @chrisck: New paper published! 🎉 What are the challenges of translating exciting AI research in healthcare to real world clinical impact…
RT @chrisck: New paper published! 🎉 What are the challenges of translating exciting AI research in healthcare to real world clinical impact…
Great work Chris! It’s reassuring to see that people at the coal face in implementing clinical #AI (ie you!) are really engaging so thoughtfully with these challenges
RT @chrisck: New paper published! 🎉 What are the challenges of translating exciting AI research in healthcare to real world clinical impact…
RT @chrisck: New paper published! 🎉 What are the challenges of translating exciting AI research in healthcare to real world clinical impact…
New paper published! 🎉 What are the challenges of translating exciting AI research in healthcare to real world clinical impact? We explore the key themes in an article published in @BMCMedicine today https://t.co/I3jXmWK1ex https://t.co/HTGA986wex
Key challenges for delivering clinical impact with artificial intelligence https://t.co/Qcslvpenuf
RT @Dominic1King: In this article with Google Health colleagues (led by @chrisck) we explore the important challenges in translating exciti…
RT @Dominic1King: In this article with Google Health colleagues (led by @chrisck) we explore the important challenges in translating exciti…
RT @Dominic1King: In this article with Google Health colleagues (led by @chrisck) we explore the important challenges in translating exciti…
Key challenges for delivering clinical impactful #AI https://t.co/QsdpwuW5VY
In this article with Google Health colleagues (led by @chrisck) we explore the important challenges in translating exciting AI healthcare research to the clinic/bedside/community. https://t.co/6DBPUcukvE