Latest AI and machine learning research in work force for healthcare professionals.
OBJECTIVES: To systematically identify, appraise and synthesise artificial intelligence (AI) and machine-learning (ML) models that predict treatment response and clinical outcomes after intravesical bacillus Calmette-Guérin (BCG) in non-muscle-invasive bladder cancer (NMIBC), a setting in which current risk calculators underperform, and identifying non-responders has become urgent as alternatives ...
Materials science is underpinned by structure-property relationships that govern the function of a material. These relationships can be encoded into algorithms and integrated into machine-learning models that enable the prediction of materials and their cognate properties. However, machine-learning models are largely being trained on computed data owing to a worldwide shortage of real-world (exper...
MOTIVATION: Protein conformation generation remains a fundamental challenge in structural biology and machine learning. Proteins are highly dynamic ma...
WEE1 kinase, a critical regulator of the G2/M checkpoint, represents a validated therapeutic target in tumors harboring defects in DNA damage response...
The global burden of cancer is significant, with millions of new diagnoses expected annually, necessitating highly coordinated and patient-centered ca...
Pediatric bipolar disorder is challenging to diagnose accurately due to symptom heterogeneity. More standardized and data-driven approaches are needed...
The integration of artificial intelligence and robotics into clinical medicine is no longer a question of whether but of how, and physicians currently...
BACKGROUND: Widespread and sustained uptake of AI-based clinical decision support systems (CDSSs) in real-world health care settings is uncommon, desp...
INTRODUCTION AND AIMS: Interpreting condylar osseous changes on CBCT is challenging for general practitioners. This study evaluated the 'zero-shot' di...
BackgroundMoral distress is common among ICU nurses and has been linked to burnout, diminished care quality, and turnover. Which factors matter most -...
Facial recognition (FR) models are vulnerable to adversarial attacks, in which attackers manipulate facial images to expose system vulnerabilities, un...
The development of generalist artificial intelligence (AI) models for radiology is hindered by a lack of large-scale, three-dimensional (3D) imaging d...
Federal research funding shapes the direction, diversity, and impact of the US scientific enterprise. Large language models (LLMs) are rapidly diffusi...
BACKGROUND: Chagas disease (ChD), a neglected cardiovascular condition, affects 7.5 to 10.5 million people worldwide. Opportunistic screening during r...
Microscopy combined with local spectroscopy is widely used to correlate nanoscale structure with functional properties in materials, but conventional ...
BACKGROUND: Digital health technologies are transforming healthcare. There is limited research describing how these technologies have been applied by ...
The adaptive immune system monitors cellular integrity by recognizing short peptides from intracellular proteins presented on major histocompatibility...
The integration of artificial intelligence (AI) into athletic training is accelerating, yet its psychological implications for athletes remain insuffi...
PURPOSE: This review explores how e-health interventions are utilized within neonatal intensive care units to support nursing practice, with particula...
Retention of highly qualified physicians remains a critical priority in rheumatology and the broader medical field due to persistent physician shortag...