Computational modelling, machine learning, and broader artificial (AI) intelligence approaches are now key approaches used to understanding and predicting ...

The transition between wakefulness and states of reduced consciousness, whether pharmacologically induced via anesthesia or pathologically necessitated by ...

AI thrives on data but feeding it the right data is harder than it seems. As enterprises scale their AI initiatives, they face the challenge of managing diverse data pipelines, ensuring proximity to ...

In the search for new drugs, artificial intelligence in the form of diffusion models is being used in drug design. What ...

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 the University of Oregon have developed an artificial intelligence tool that can read genetic code the way large language models like ChatGPT read text. Scanning the genome for ...

Climate change, extreme weather events, unprecedented records in temperatures and higher, acidic oceans make it difficult to predict the long-term fate of modern crop varieties. “With these kinds of ...

Researchers use machine learning and genetic analysis to uncover type 1 diabetes risk factors, improving prediction accuracy ...

A new system for forecasting weather and predicting future climate uses artificial intelligence (AI) to achieve results comparable with the best existing models while using much less computer power, ...

PLSKB: An Interactive Knowledge Base to Support Diagnosis, Treatment, and Screening of Lynch Syndrome on the Basis of Precision Oncology We used an innovative machine learning approach to analyze ...