Latest AI and machine learning research in work force for healthcare professionals.
Grassland canopy height is one of the most important traits for determining plant diversity and community structure, directly affecting the resource use efficiency of livestock in grassland ecosystems. However, broad-scale changes in grassland canopy height are seldom reported due to the complex effects of species aggregation on both interspecific and intraspecific structures. Here, we decouple gr...
CO2 from flue gas is central to mitigating fossil-fuel-derived emissions, where adsorbent performance directly dictates process energy efficiency and process cost. Although machine learning (ML) has emerged as a powerful tool for accelerating adsorbent discovery, its predictive accuracy is fundamentally limited by the physical reliability of the underlying training data, a manifestation of the "ga...
Computed tomography (CT) is a major medical imaging modality. Clinical CT scenarios, such as low-dose screening, sparse-view scanning, and metal impla...
Incomplete multiview clustering (IMVC) faces significant challenges due to missing data and inherent view discrepancies. While deep neural networks of...
BACKGROUND: The contradiction between the surging demand for mental health services and the shortage of professional resources is becoming increasingl...
UNLABELLED: Cystic fibrosis (CF) alters gut physiology, yet its impact on microbial communities across colonic regions (ascending, transverse, descend...
Artificial intelligence (AI) is rapidly transforming healthcare delivery, logistics, and operational decision-making across the Military Health System...
Congenital heart disease (CHD) is the leading cause of neonatal mortality worldwide, making early and accurate diagnosis crucial. In resource-constrai...
Bladder cancer carries one of the highest lifetime costs among malignancies, and accurate distinction between non-muscle-invasive and muscle-invasive ...
BACKGROUND/AIMS: Global megatrends, including population growth, interconnectedness and artificial intelligence, are already shaping the clinical tria...
BACKGROUND/AIMS: Patients have largely been excluded from discussions on the use of their health data in developing medical artificial intelligence (A...
Lack of nutrient-rich food consumption is considered an important underlying factor affecting the healthy development of children, and can lead to dev...
Machine learning interatomic potentials (MLIPs), also known as machine learning force fields (MLFFs), offer scalable means of simulating complex syste...
Artificial intelligence (AI) is rapidly advancing respiratory disease management, from diagnosis to population lung health. This scoping review synthe...
INTRODUCTION: Artificial intelligence (AI) is rapidly transforming medical diagnosis worldwide, but its adoption remains limited in Africa, particular...
OBJECTIVE: To evaluate radiologists' opinions on the clinical applications of artificial intelligence (AI), especially AI-based computer-aided detecti...
Accurate models for electrostatic and induction interactions are fundamental for computational molecular science, including drug discovery, studies of...
Plant diversity is essential for regulating ecosystem functions, yet its global-scale relationship with soil respiration, a critical component of the ...
This study explores strategies to guide the generation of polyimides with high glass transition temperatures (Tg > 750 K) through reinforcement learni...
BACKGROUND AND OBJECTIVE: Neuroimaging AI systems increasingly influence clinical decisions, yet demographic exclusions in training datasets may compr...