A biology-guided artificial intelligence model applied to routine pathology slides accurately predicted outcomes and response to immunotherapy in patients with metastatic non-small cell lung cancer ...

Researchers have developed a new artificial intelligence (AI) model that can more accurately predict how proteins interact ...

In the world of highly competitive digital platforms, the main attraction for the business is the user's attention. In some ...

Artificial intelligence and machine learning are reshaping diabetes prevention, diagnosis, and management across the care continuum. Continuous glucose ...

A new study published in Genome Research presents an interpretable artificial intelligence framework that improves both the accuracy and transparency of genomic prediction, a key challenge in fields ...

Processing data closer to its source (edge computing) combined with AI allows for faster analysis and decision-making in preventative maintenance, as well as enhances data security. The work flows in ...

Abstract: This paper proposes an intelligent tuning framework for a boost converter connected to a photovoltaic (PV) system using a generalized Model Predictive Control (MPC) strategy integrated with ...

The techniques that have served marketers for over fifty years are evolving rapidly, driven by artificial intelligence, increasing market volatility and a fundamental shift in what we expect ...

Self-supervised reinforcement learning is a technique where agents learn useful representations and skills from the environment through self-generated tasks, such as predicting next states or learning ...

The current microgrids are experiencing growing difficulties in voltage stability and operational capacity, particularly with constant power loads (CPLs), leading to negative impedance behavior and ...

1 Department of Mathematics & Statistical Sciences, Jackson State University, Jackson, MS, USA. 2 Department of Public Health, California State University, Fullerton ...