Cleveland Clinic and IBM researchers are using quantum computing to tackle one of the most challenging problems in immuno-oncology: predicting which tumor mutations will trigger an immune response.
BACKGROUND: Screening for atrial fibrillation (AF) on the basis of AF risk may be more effective. We aimed to develop, ...
A machine-learning model developed by Weill Cornell Medicine investigators may provide clinicians with an early warning of a complication that can occur late in pregnancy. Preeclampsia is a sudden ...
A recent study published in the Journal of Hepatology demonstrated that a machine learning–based pan-elastography model can ...
Two complementary predictors (DAAE-M and ELIE) estimate individualized 5-year progression risk using routine clinical data, extending the prior DAAE framework beyond static baseline risk. Registry ...
A new study shows that machine-learning models can accurately predict daily crop transpiration using direct plant measurements and environmental data. By training models on seven years of ...
Enhancing Readability of Lay Abstracts and Summaries for Urologic Oncology Literature Using Generative Artificial Intelligence: BRIDGE-AI 6 Randomized Controlled Trial We trained and tested ML systems ...
Predicting earthquakes has long been an unattainable fantasy. Factors like odd animal behaviors that have historically been thought to forebode earthquakes are not supported by empirical evidence. As ...
A large study found that a LightGBM machine learning model accurately predicted survival and early death risk in patients ...
AgPlenus Ltd., a company developing novel, sustainable crop protection products and a subsidiary of Evogene Ltd. (NASDAQ: EVGN) (TASE: EVGN), today announced the launch of its Antifungal Potency ...
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