Researchers at University of Jyväskylä (Finland) advance understanding of gold nanocluster behavior at elevated temperatures ...
Around the world, millions of families have suffered forcible separation, through war, trafficking, natural disasters, or ...
The team utilized machine learning to analyze public data from the National Health and Nutrition Examination Survey.
Interpretable AI model could offer new insights into why medicines cause certain side effects, helping to improve future drug safety predictions.
2don MSN
Automating microfluidic chip design: Hybrid approach combines machine learning with fluid mechanics
Researchers led by Assoc. Prof. Dr. Savaş Taşoğlu from the Department of Mechanical Engineering at Koç University have ...
Machine learning careers offer strong salary growth across Indian industriesReal projects and deployment skills matter more ...
A novel machine learning version of the Opioid Risk Tool provides high precision screening for opioid use disorder in chronic pain patients.
Background Early graft failure within 90 postoperative days is the leading cause of mortality after heart transplantation. Existing risk scores, based on linear regression, often struggle to capture ...
Schizophrenia is a severe and often highly debilitating psychiatric disorder characterized by distorted emotions, thinking patterns and altered perceptions of reality, as well as mental impairments.
Recent developments in machine learning techniques have been supported by the continuous increase in availability of high-performance computational resources and data. While large volumes of data are ...
Electrocatalysis sits at the heart of clean hydrogen production, fuel cells, and carbon dioxide conversion, yet progress ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results