Responsible AI involves designing machine learning systems that are transparent, fair, and accountable. In the context of healthcare, responsible AI also includes protecting patient privacy, ensuring ...
The battlefield is no longer just a physical space of troops and artillery; it is a vast, invisible network of data, sensors, and machine learning models. In the current Iran-Israel conflict, AI is ...
The use of machine learning (ML) and artificial intelligence (AI) in power converters represents the latest development in ...
Machine learning algorithms may accurately predict inborn errors of immunity (IEI) in children with persistently low serum IgE.
Researchers report that the integration of machine learning and Internet of Things (IoT) technologies is enabling a new generation of intelligent industrial environments capable of real-time ...
The frequency of substance use, early age of initiation, and cannabis-related memory impairments are among the primary factors contributing to driving under the influence, according to a new analysis ...
In A Nutshell Researchers used a machine learning model to rank all 50 U.S. states and Washington, D.C. by socioeconomic vulnerability to flu-like illness, finding wide regional variation in risk.
A retinal image could help doctors quickly distinguish between similar neurodegenerative diseases such as ALS and Alzheimer's disease, and with ...
Traditional lending relies on collateral and a financial history that productive smallholder farmers may find difficult to ...
Finalists in the Society for Science and Regeneron $1.8 million science competition are increasingly turning to machine learning, and organizers are balancing innovation with misuse.
Dr. Melanie Campbell and graduate student Lyndsy Acheson study an image of a retina. They are looking for protein deposits found in association with brain diseases, such as Alzheimer's, FTLD-TDP and ...
A machine learning-driven framework accurately predicts MPA exposure and supports individualized dosing in childhood-onset LN.