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@Radiology_AI 10 months ago
Differences in data distribution may affect federated #DeepLearning model performance in medical image segmentation https://doi.org/10.1148/ryai.220082 @ND_CSE @hku_science @ZJU_China #FederatedLearning #AI #MachineLearning #AIME23 #AIME2023 https://t.co/Sg0Y2jheGy
@freddytn 1 year ago
In #machinelearning, synthetic data can offer real performance improvements Models trained on synthetic data ➡️ eliminate privacy, copyright, & ethical concerns from using real data @MIT_CSAIL @MITEECS @MIT_SCC @MITIBMLab #health #healthcare #medicine https://news.mit.edu/2022/synthetic-data-ai-improvements-1103
@DiagnosingML 2 years ago
External validation of a widely implemented Sepsis Prediction Model shows significantly poorer performance than reported by developers. https://ja.ma/3wXhG3s via @JAMAInternalMed #machinelearning #ethics #ethicalAI #health #AI #medicine @stacymcarter
@f2harrell 5 years ago
New guest blog article by my colleague @DrewLevy on the importance of predictive performance metric choices when evaluating #MachineLearning algorithms in medicine: http://fharrell.com/post/mlconfusion
@DSMeu 5 years ago
New medicines could be developed faster thanks to high performance computing & #machinelearning. Read this story about an EU-supported project http://bit.ly/2Or4zRH #EuroHPC #HPC #HealthTech https://t.co/gf62ur9HCL
@curtlanglotz 6 years ago
Such a pleasure to speak this morning to #RadISummit18 on intersection of #AI, medical imaging, and performance improvement. Bottom line: Data generated by performance improvement projects can train #machinelearning systems to support high-reliability processes. https://twitter.com/AKrishnarajMD/status/962366493764632576