Latest AI and machine learning research in surveys for healthcare professionals.
This article presents a survey-based dataset examining hybrid car adoption behaviour and sustainability-related perceptions among consumers in Bangladesh. The dataset was developed to investigate factors influencing behavioural intention toward hybrid vehicle adoption using the Unified Theory of Acceptance and Use of Technology (UTAUT2) framework together with additional sustainability-oriented be...
Depression is a common comorbidity in individuals with diabetes and is associated with adverse clinical outcomes. Early identification of high-risk individuals remains challenging due to the multifactorial and nonlinear nature of depression risk. Machine learning (ML) may enhance risk prediction but requires appropriate handling of class imbalance and sufficient interpretability for clinical appli...
AIMS: We aimed to develop a machine learning-based tool for accurate quantitative prediction of diuretic response in acute heart failure (AHF). METHOD...
BACKGROUND: Patients increasingly use the Internet and artificial intelligence (AI) platforms ChatGPT for medical information, raising concerns about ...
With the rapid expansion of artificial intelligence (AI) in education, valid tools are needed to assess teachers' readiness for anticipatory, adaptive...
Phishing is a fraudulent activity that includes tricking folks into disclosing personal information by impersonating a legitimate individual or organi...
To systematically review Machine Learning (ML) fracture risk prediction models developed solely using administrative data, evaluating their developmen...
BACKGROUND: Artificial intelligence (AI) is increasingly integrated into healthcare education and clinical practice. Understanding health sciences stu...
OBJECTIVE: This study aimed to evaluate the validity and reliability of responses generated by GPT-4o, Microsoft Copilot, Google Gemini, and DeepSeek ...
BACKGROUND: Panoramic radiographs are used routinely to screen dental conditions and treatment patterns. Recently, numerous studies have suggested tha...
Identifying gene-disease associations (GDAs) remains a fundamental challenge in biomedical research due to the enormous combinatorial space of candida...
BACKGROUND AND OBJECTIVE: Modeling cerebral aneurysms using patient-specific geometries demands significant computational resources, particularly when...
BACKGROUND: Eating disorders (EDs) are a growing global health concern and are increasingly associated with negative body-image perceptions linked to ...
BACKGROUND: Despite rapid integration of AI in healthcare, formal AI education remains limited in health professional curricula globally, particularly...
PURPOSE: This paper seeks to improve the reliability and quality of operation of the critical medical equipment methods through the combination of fai...
Aiming at an intelligent point-of-care imaging technology for rheumatology clinics, a fully automatic 3D photoacoustic (PA) and ultrasound (US) dual-m...
We present the Dine In or Take Out Dataset, a virtual reality dataset collected using a Meta Quest Pro, to understand how predominantly Gen Z individu...
BackgroundArtificial intelligence (AI) may offer potential to augment risk assessment and expand personalised treatment in prison psychiatry. In Queen...
Artificial intelligence (AI) is increasingly integrated into burn care for triage, burn-depth assessment, prognostic scoring, pain management, and tel...
BACKGROUND: Population aging has become a critical global challenge, with South Korea entering a super-aged society and facing rapidly increasing heal...