Researchers at Stanford Medicine have developed a new customizable AI tool called PathChat, which can be trained by pathologists to identify different cells and offer diagnostic insights. This 'human-in-the-loop' framework aims to overcome the limitations of off-the-shelf AI models in pathology. The AI assistant, featured in articles by Nature, Stat News, and VentureBeat, has shown to be better and faster than both human pathologists and standalone AI systems. PathChat can analyze microscopy images, converse with pathologists about tumors, and provide diagnoses. The tool's performance on diagnostic questions and responses in pathology has been highlighted, showcasing its potential to revolutionize the field. The research involved contributions from BrighamWomens and was described in natBME.
Customizable #AI tool developed at Stanford Medicine helps #pathologists identify diseased cells https://t.co/q4rWFsWRlW
A #pathologist–#AI collaboration framework for enhancing diagnostic accuracies and efficiencies https://t.co/sHFLpEcngN
Thanks to @taryn_plumb for covering our PathChat @Nature article (https://t.co/sYSpFCBmat) in @VentureBeat - New medical LLM, PathChat, can talk to pathologists about tumors, offer diagnoses https://t.co/pdMaWffNPP
Excellent @Stanford article discussing our new approach to personalize #AI for pathologists. Thank you @StanfordMed and @sarahcpwilliams for highlighting our work! https://t.co/zlRHksuYqR
Most medical #AI programs are one-size-fits-all, but https://t.co/3w1uh99bGo can be custom-trained by pathologists to ID different cells. @james_y_zou, Thomas Montine and colleagues at @StanfordMed @StanfordPath described the tool this week in @natBME. https://t.co/NyfZXFB6SK
PathChat A Multimodal AI for Human Pathology PathChat, a vision-language generalist AI assistant, is introduced, showcasing its performance on diagnostic questions and responses in pathology. AI in Healthcare #GenAI #TechBio #HealthAI #MedTwitter #MedicalAI #AIRegulation… https://t.co/BqDocOyLc7
🔬Revolutionizing pathology with #AI: @Stanford researchers developed a “human-in-the-loop” framework called https://t.co/Kb6qOxFnjt to overcome limitations of off-the-shelf AI models for pathology. They found it to be better and faster than humans or AI working alone. 1/4 https://t.co/Zo7yKdHxDf
Thanks to @brittanytrang for covering our PathChat @Nature article (https://t.co/sYSpFCBmat) in @statnews - AI for biopsies can analyze microscopy images, talk to pathologists about your tumor https://t.co/daaNhgKvt2 @Harvard @harvardmed @BrighamWomens
Thanks to @brittanytrang for covering our PathChat @Nature article (https://t.co/sYSpFCBmat) in @statnews - AI for biopsies can analyze microscopy images, talk to pathologists about your tumor https://t.co/daaNhgKvt2