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Federated benchmarking of medical artificial intelligence with MedPerf

Medical artificial intelligence (AI) has tremendous potential to advance healthcare by supporting and contributing to the evidence-based practice of medicine, personalizing patient treatment, reducing costs, and improving both healthcare provider and patient experience. Unlocking this potential requires systematic, quantitative evaluation of the performance of medical AI models on large-scale, heterogeneous data capturing diverse patient populations. Here, to meet this need, we introduce MedPerf, an open platform for benchmarking AI models in the medical domain. MedPerf focuses on enabling federated evaluation of AI models, by securely distributing them to different facilities, such as healthcare organizations. This process of bringing the model to the data empowers each facility to assess and verify the performance of AI models in an efficient and human-supervised process, while prioritizing privacy. We describe the current challenges healthcare and AI communities face, the need for a ....

United Kingdom , Flower Labs University Of Cambridge , Microsoft Research , Open Federated Learning , Federated Tumor Segmentation ,

MLCommons launches a new platform to benchmark AI medical models

With the pandemic acting as an accelerant, the healthcare industry is embracing AI enthusiastically. According to a 2020 survey by Optum, 80% of healthcare organizations have an AI strategy in place, while another 15% are planning to launch one. Google recently unveiled Med-PaLM 2, an AI model designed to answer medical questions and find insights in medical texts. ....

Renato Umeton , Duke University , Dana Farber Cancer Institute , Mlcommons Medical Working Group , Federated Tumor Segmentation , Medical Working Group , Yahoo Finance , Healthcare Organizations , Medical Models , Medical Data , Medical Model , Healthcare Industry , Medical Working Group ,