A new machine learning model built using a simple and interpretable approach predicts in-hospital death in patients with acute liver failure and reveals top risk drivers.
An AI model with the potential to transform cervical spondylosis diagnosis by spotting subtle vertebral changes quickly and accurately.
LCGC International’s interview series on the evolving role of artificial intelligence (AI)/machine learning (ML) in separation science continues with Boudewijn Hollebrands from Unilever Foods R&D, ...
The severity of symptoms in posttraumatic stress disorder (PTSD) varies greatly across individuals in the first year after trauma and it remains difficult to predict whether someone might worsen, ...
Researchers at Google have developed a new AI paradigm aimed at solving one of the biggest limitations in today’s large language models: their inability to learn or update their knowledge after ...
People's decisions are known to be influenced by past experiences, including the outcomes of earlier choices. For over a century, psychologists have been trying to shed light on the processes ...
Machine learning can predict many things, but can it predict who will develop schizophrenia years before the average diagnosis time?
Implications of EGFR expression in MAPK dependency and adaptive immunity status of EGFR-mutated lung adenocarcinoma. Baseline RADAR score and optimal threshold of predicting relapse within one year ...
Physiologically Based Pharmacokinetic Model to Assess the Drug-Drug-Gene Interaction Potential of Belzutifan in Combination With Cyclin-Dependent Kinase 4/6 Inhibitors A total of 14,177 patients were ...
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