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For physicists, its cool to work at the LHC (Large Hadron Collider). For a data scientist doing causal inference, its cool to work at an LHC (Large Hospital Collider).

Colouring book self-supervised learning bayesianbiologist.com/2022/03/25/col…

Fighting sepsis is an ongoing battle and for patients with hospital acquired sepsis, capacity strain may contribute to antimicrobial delays. Learn more about this important underlying factor in new research from PAIR fellow Jennifer Ginestra, MD, MS. Gary Weissman pubmed.ncbi.nlm.nih.gov/35312462/

🚨NEW🚨 in PLOS One led by Eric H. Li: Suppose a validated #MachineLearning algorithm identifies that your patient is at risk for a bad outcome. How do you respond? The answer: It depends on what type of doctor you are... journals.plos.org/plosone/articl…

Jensen's Ginequality.

Today! Senior AI Scientist Vaughn Spurrier takes the #ECDP2022 stage to present "Automated Quality Control of Whole Slide Images Using Artificial Intelligence." Catch his presentation in Ballroom II at 9:40 CEST.

Former lab-mate doing great work. Making my day :) Way to go, Dr. Ayaz Hyder, PhD !

Just announced! Unilabs has selected @ProsciaInc's DermAI to advance its aspiration of becoming the most digitally-driven diagnostic group. Read the full release for more. bit.ly/3ePH2Mw

Our work on predicting pathologist concordance of melanoma diagnosis detection is up! Helping identify the 'hard cases' will allow efficient routing to specialist, improving accuracy and reducing time-to-diagnosis.

🚨NEW in AMIA w/ Jinbo Chen Amol Navathe Likelihood T. Prior Kate Courtright + colleagues Penn🚨 How did the #COVID19 #pandemic impact healthcare #algorithms? We show that COVID utilization "shock"➡️long-lasting declines in algorithm performance🧵academic.oup.com/jamia/advance-…

🚨 NEW 🚨 in JCO Clinical Cancer Informatics: #MachineLearning algorithms to predict mortality or adverse events are often based on routinely-collected administrative #data. Big limitation. How does incorporating the #patient voice into predictions help? Answer: A lot! ascopubs.org/doi/full/10.12…

From London to the blog - Sr. AI Scientist Likelihood T. Prior recaps his poster presentation from #DigitalPathology & AI Congress: Europe. Get a look at our research demonstrating the promise of AI to identify melanoma cases w/ the highest diagnostic uncertainty. bit.ly/3BOLHHq

Read more about our latest research wherein we demonstrate the how AI can identify melanoma cases with the highest diagnostic uncertainty. bit.ly/3BOLHHq @ProsciaInc Sean Grullon Julianna Ianni Vaughn Spurrier

Mon collègue Likelihood T. Prior a présenté une affiche sur l'#IA qui prédit la discordance diagnostique pour les cas de #mélanome lors du récent Digital Pathology & AI Congress (Europe) et l'a récapitulée sur le blog de @ProsciaInc : proscia.com/dissecting-dia…

Our CEO @davidwest_Irl shares a message on our FDA 510(k) clearance. Want to learn more? Join our webinar on March 8. bit.ly/3ume5Ag