Latest AI and machine learning research in surveys for healthcare professionals.
BACKGROUND: Climate variability is increasingly recognized as a driver of child undernutrition, yet the non-linear relationships between specific climatic variables and nutrition remain unclear. This study uses machine learning to identify and quantify key climatic predictors of undernutrition among children. METHODS: In a mixed-method approach, a cross-sectional study assessed nutrition and child...
INTRODUCTION: Diagnosis of affective disorders among adolescent population links with the high risk of suicide attempt. The use of clinical psychological scales and biological markers may help to understand the background of suicidal process. Here we present the exploratory data study on retrospective suicide attempt risk factors and classification model of diagnosis conversion from major depressi...
BACKGROUND: Growth of generative artificial intelligence (GenAI) has exploded in recent years. Many have noted its substantial potential to increase a...
BACKGROUND: Healthcare Artificial Intelligence (AI) offers transformative potential but often inherits biases from training data, worsening disparitie...
PURPOSE: This study aims to clarify the associations between task complexity and Artificial Intelligence (AI) dependency among university students and...
Reconstructing speech from neural recordings is crucial for understanding human speech coding and developing brain-computer interfaces (BCIs). However...
This study develops and evaluates ETHICS, a concise, clinician-facing ethical protocol for the routine use of machine learning (ML) in healthcare. Usi...
BACKGROUND/OBJECTIVES: Patient messaging portals are widely used in clinical practice and are linked to improved patient outcomes, but they are also a...
BACKGROUND: The integration of artificial intelligence (AI) into clinical practice is contingent on public trust. This trust often depends on physicia...
Artificial intelligence (AI) rapidly transforms biological research and STEM education by enabling automated data collection and analysis. In order to...
Background: Real-world performance of radiology artificial intelligence (AI) applications frequently diverges from previously reported results, creati...
The rapid adoption of generative artificial intelligence (GenAI) in nursing education presents urgent ethical challenges, particularly as students emp...
Conventional techniques in drug discovery are time-consuming and less accurate due to the vast chemical space and associated uncertainty. Artificial i...
RÃos-Gallardo, PT, Carranza-GarcÃa, LE, Dietze-Hermosa, M, Gonzalez, MP, Balsalobre-Fernández, C, Dorgo, S, and Montalvo, S. Validity and reliability ...
PURPOSE: This study aimed to develop a cluster-based measure of multiple co-occurring social determinants of health by applying unsupervised machine l...
BACKGROUND: Artificial intelligence (AI) tools are widely and freely available for clinical use. Understanding hospitalists' real-world adoption patte...
OBJECTIVES: To develop a deep learning-based framework to automate sector classification of unerupted maxillary canines (UMCs), assessing its accuracy...
PURPOSE: As artificial intelligence (AI) models evolve into their next generations, their application in specialized medical fields requires rigorous ...
BACKGROUND: Health care organizations have started to implement artificial intelligence-powered ambient scribe technology in clinical documentation wo...
BACKGROUND AND STUDY AIMS: Accurate determination of colorectal polyp size is critical for surveillance recommendations and for generating reliable gr...