Latest AI and machine learning research in surveys for healthcare professionals.
The vast reaction data within scientific literature represents a rich resource for training predictive machine learning models. However, this resource is fundamentally compromised by a pervasive selection and reporting bias, resulting in imbalanced data sets. In this work, we introduce "Positivity is All You Need" (PAYN), a machine learning framework that addresses this data-scarcity problem by le...
Drug response prediction (DRP), accounting for the diverse biological characteristics of cancer types that affect sensitivity or resistance to treatment, is crucial for anticancer drug selection and discovery. Although numerous deep learning models for DRP have been developed, it has not been investigated whether these models can maintain reliable predictive power when applied to omics datasets no...
With the increasing use of digital platforms for spread of information, political news has some of the most skewed sources which has confused people o...
OBJECTIVE: Frequent and objective assessment of ataxia severity is essential for tracking disease progression and evaluating the effectiveness of pote...
Adolescent mental health is foundational to personal development, yet it faces escalating challenges globally. While traditional assessment methods la...
Purpose To develop a deep learning model for segmenting pectoralis muscle volume (PMV) at CT and evaluate the reproducibility, group differences, and ...
BACKGROUND: The role of artificial intelligence (AI) in medical care has become increasingly prominent. There is an urgent need to integrate the cross...
Purpose Artificial intelligence (AI) is increasingly used in health professions education, yet little is known about dental hygiene students' knowledg...
Recent advancements in artificial intelligence have led to increased interest in predictive modeling across various domains, including medicine. Altho...
BACKGROUND: As artificial intelligence (AI) becomes increasingly integrated into education, understanding student perceptions of AI-generated support ...
Evidence-based Paralympic classification must limit impairment-related advantages. World Shooting Para Sport classification, based on manual muscle te...
RATIONALE AND OBJECTIVES: This study evaluates the performance of ChatGPT, a large language model (LLM), in selecting appropriate imaging modalities f...
OBJECTIVE: Recent growth of online research has been accompanied by an increase in reports of fraudulent participants, which can significantly compris...
OBJECTIVES: Artificial Intelligence models are increasingly used in health care, yet global performance metrics can mask variations in reliability acr...
BACKGROUND: Many factors cause kidney transplant graft failure. To identify at-risk patients and tailor treatment, failure risks must be accurately pr...
Artificial intelligence is emerging as a powerful tool for improving mental health research and care, offering opportunities for early intervention, p...
INTRODUCTION: Informed consent is essential to surgical care yet often burdens clinicians. Recent studies suggest that large language models can strea...
Artificial intelligence (AI) is increasingly integrated into breast imaging workflows, offering the potential to enhance diagnostic accuracy, efficien...
This study aimed to evaluate and compare the responses provided by ChatGPT-4o, Google Gemini (2.0 Flash) and Microsoft Copilot to frequently asked que...
BACKGROUND: Generative AI (GenAI) has increasingly been used in ways to support health professions education but the utility of it to support research...