As data privacy collides with AI’s rapid expansion, the Berkeley-trained technologist explains how a new generation of models ...
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A scoping review shows machine learning models may help predict response to biologic and targeted synthetic DMARDs in ...
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New method improves the reliability of statistical estimations
MIT researchers have developed a method that generates more accurate uncertainty measures for certain types of estimation.
MS student Karina Zadorozhny presented research she conducted during an internship at Amsterdam-based Pacmed during the 6th International Workshop on Health Intelligence Karina Zadorozhny’s experience ...
Experts are increasingly turning to machine learning to predict antibiotic resistance in pathogens. With its help, resistance ...
A new technical paper titled “Post-hoc Uncertainty Learning using a Dirichlet Meta-Model” was published (preprint) by researchers at MIT, University of Florida, and MIT-IBM Watson AI Lab (IBM Research ...
From SOCs to smart cameras, AI-driven systems are transforming security from a reactive to a predictive approach. This ...
How can systems be designed to guard against unexpected downtime? How does system reliability impact product development? In what ways can artificial intelligence and machine learning improve system ...
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