The new capabilities are available starting today, with some features in beta or public preview.
A machine learning model can use patient-reported data and remote therapeutic monitoring to accurately assess low disease activity in rheumatoid arthritis, according to data presented at ACR ...
This predictive model built on readily acquired clinical data provides encouraging results for the detection of residual disease. External validation and prospective studies implementing the model in ...
Ex vivo lung perfusion (EVLP) provides a platform for testing therapies but faces challenges in standardizing drug evaluation. At AAPS PharmSci 360, Xuanzi Zhou says digital twins accurately predict ...
Southwest Research Institute (SwRI) has developed a method to automate the calibration of heavy-duty diesel truck emissions ...
Georgia Southern University researchers develop a machine learning model with 97.97% accuracy in earthquake forecasting. STATESBORO, GA, UNITED STATES, October 29 ...
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Machine learning improves accuracy of climate models—particularly for compound extreme events
Researchers have devised a new machine learning method to improve large-scale climate model projections and demonstrated that the new tool makes the models more accurate at both the global and ...
A machine learning model using basic clinical data can predict PH risk, identifying key predictors like low hemoglobin and elevated NT-proBNP. Researchers have developed a machine learning model that ...
Their study is centred around answering three research questions: Do ANNs perform better than the traditional multiple regression models in the prediction of lighting parameters and energy demand of ...
A rotating cylinder with its side cut away to expose the core, showing patches of purple, blue, green, yellow, and orange that are dense in the middle and more diffuse toward the edges. This rotating ...
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