Prevention of medical errors

Lung cancer multimodal auxiliary diagnosis based on entropy weight decision fusion.

BACKGROUND: Lung cancer ranks among the most lethal malignancies globally, and its traditional diagnosis suffers from strong subjectivity, high misdiagnosis rates and uneven medical resources. To overcome the poor feature alignment caused by simply concatenating CT images and clinical text, this paper proposes a lung cancer multimodal auxiliary diagnosis model based on entropy weight decision fusi...

AI Educational Engagement Patterns and Their Association With Attitudes Toward AI Integration in Anatomical Science Education: A Cross-Sectional Study.

Artificial intelligence (AI) is being increasingly integrated into education. Our study aims to explore the association between medical students' learning patterns and their attitudes toward AI-integrated teaching in anatomical sciences. A cross-sectional study was conducted among undergraduate second to sixth year medical students from a single accredited medical program (MD) at Al-Balqa Applied ...

Ethical Considerations in Personal Health Large Language Models.

Personal health large language models (PH-LLMs) have rapidly evolved from research prototypes into consumer-facing, data-linked systems that support s...

The Warmth of Medicine: The Irreplaceability of Doctors in the Era of Artificial Intelligence.

This article argues that despite the remarkable advances of artificial intelligence (AI) in medicine -including demonstrated capabilities in image rec...

Computer-aided diagnosis system for thoracic computed tomography of rib fractures in older emergency patients: A preliminary study.

The peculiarities of older individuals related to osteoporosis and hyperostosis may lead to a higher rate of misdiagnosis of rib fractures on computed...

Bridging the Disclosure Gap: AI's Potential Role in Suicide Prevention.

Conversational artificial intelligence (AI) tools-specifically, general-purpose large language models-are increasingly used by individuals to disclose...

MedQM: Medical Blind Image Quality Assessment for MLLM Vision.

In recent years, deep learning models represented by multi-modal large language models (MLLMs) have been widely applied in the medical domain. As imag...

Implementing Digital Respiratory Technologies for People With Respiratory Conditions: Scoping Review.

BACKGROUND: Digital health offers opportunities for safe, equitable, and accessible care, and its integration into respiratory care is a strategic pri...

Advances in evaluating and delivering nontechnical skills training: The use of simulation, robotics, artificial intelligence and virtual reality.

PURPOSE OF REVIEW: Nontechnical skills (NTS), such as communication, leadership, and situational awareness, are essential for ensuring surgical safety...

Artificial intelligence and machine learning in robotic, teleoperated, and remote surgery: a bibliometric and knowledge mapping analysis (2015-2025).

Artificial intelligence (AI) and machine learning (ML) technologies are rapidly transforming telesurgery by enhancing robotic-assisted surgical system...

Large language models integrated into brain-computer interfaces for communication and control: a systematic review.

Large language models (LLMs) are starting to be coupled with brain-computer interfaces (BCIs) for assistive communication, but the resulting systems d...

A Critical Systematic Review of Modelling Approaches and Methodologies used in Hyperlipidaemia Economic Evaluations.

BACKGROUND AND OBJECTIVES: Health economic modelling integrates evidence from multiple sources and relies on transparency to support reimbursement dec...

A scoping review of traditional and artificial intelligence methods in malaria diagnostics.

Malaria remains a substantial global health burden with current diagnostics having notable limitations. Microscopy is labor-intensive and operator-dep...

An ensemble of deep learning models with falcon optimization assisted diabetic retinopathy diagnosis on retinal fundus images.

Diabetic Retinopathy (DR) is a prominent results of diabetes mellitus that causes abnormalities lesions in retina. If not identified at early, it may ...

Joint optimization secure and energy-efficient computation offloading framework IoT-enabled edge networks.

With the rapid growth and development of smart cities, many real-time systems have been designed to support the dynamic infrastructure of realistic an...

Development of a prediction model for infectious mononucleosis using machine learning algorithms based on blood cell analysis parameters.

BACKGROUND: Infectious mononucleosis (IM) presents with nonspecific clinical manifestations, leading to frequent misdiagnosis or delayed diagnosis, an...

Improving Trauma Triage Accuracy with Large Language Models: A Comparison to Human Expert Decisions.

BACKGROUND: Accurate prehospital trauma triage and communication determine morbidity, mortality, and system efficiency. Advancements in large language...

Training Empathetic Communication Skills in Medical Students With a Role-Prompted GPT-4o Chatbot: Quasi-Experimental Intervention Study.

BACKGROUND: There is growing concern that artificial intelligence (AI) may diminish the quality of human relationships. However, in a context of wides...

AI-assisted diagnosis of cardiac amyloidosis using electrocardiograms and echocardiography: a multicenter retrospective study in China.

BACKGROUND: Cardiac amyloidosis (CA) is an under-recognized cause of left-ventricular hypertrophy (LVH) that is often misclassified as hypertrophic ca...

FSCL-BC: Federated supervised contrastive learning for breast cancer diagnosis with high sensitivity.

BACKGROUND AND OBJECTIVE: Accurate diagnosis of breast cancer in dense breasts requires expert radiologists to examine multiple ultrasound images per ...