OBJECTIVES: To identify the factors associated with post-stroke depression (PSD) and develop a machine learning predictive model using a large dataset, considering sociodemographic, lifestyle, and clinical factors.
Hospital-acquired infections (HAIs) significantly burden global healthcare systems, exacerbated by antibiotic-resistant bacteria. Traditional infection control measures often lack consistency due to variable human compliance. This comprehensive revie...
OBJECTIVES: To explore nursing students' perceptions and understanding of artificial intelligence (AI), aiming to identify and address critical knowledge gaps to support effective integration into educational practices.
OBJECTIVES: To assess the accuracy of ChatGPT-4 Omni (GPT-4o) in biomedical statistics. The recent novel inauguration of Artificial Intelligence ChatGPT-Omni (GPT-4o), has emerged with the potential to analyze sophisticated and extensive data sets, c...
OBJECTIVES: To evaluate the role of artificial intelligence (Google Bard) in figures, scans, and image identifications and interpretations in medical education and healthcare sciences through an Objective Structured Practical Examination (OSPE) type ...
Breast imaging faces challenges with the current increase in medical imaging requests and lesions that breast screening programs can miss. Solutions to improve these challenges are being sought with the recent advancement and adoption of artificial i...
OBJECTIVES: To assess the knowledge and perception of artificial intelligence (AI) among radiology residents across Saudi Arabia and assess their interest in learning about AI.