BACKGROUND AND OBJECTIVES: Cortical lesions in multiple sclerosis (MS) severely affect cognition, but their longitudinal evolution and impact on specific cognitive functions remain understudied. This study investigates the evolution of function-speci...
BACKGROUND: Traditional risk models, such as POSSUM and OS-MS, have limited accuracy in predicting complications after bariatric surgery. Machine learning (ML) offers new opportunities for personalized risk assessment by incorporating artificial inte...
OBJECTIVE: To develop a computer algorithm for the automatic classification of basic surgical skills in laparoscopy. The ability to objectively assess the operative skills of trainees would be invaluable for the success of competency-based medical ed...
RATIONALE AND OBJECTIVES: The objective of this study was to evaluate a combination of deep learning (DL)-reconstructed parallel acquisition technique (PAT) and simultaneous multislice (SMS) acceleration imaging in comparison to conventional knee ima...
European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery
Jun 1, 2025
PURPOSE: To evaluate the diagnostic accuracy, appropriateness of additional examination recommendations, and consistency of therapeutic regimens by ChatGPT-4 and Llama2 based on real otolaryngology cases.
BACKGROUND: The National Early Warning Score is widely used in Emergency Departments for triage, primarily to predict mortality. However, its effectiveness in assessing additional clinical outcomes relevant to triage, such as patient urgency and seve...
BACKGROUND: Personal protective equipment (PPE) is a first-line transmission-based precaution for reducing the spread of nosocomial infections between health care workers (HCWs), patients, and staff. The COVID-19 pandemic highlighted a problematic sk...
PURPOSE: To compare the image quality and pulmonary nodule detectability and measurement accuracy between deep learning reconstruction (DLR) and hybrid iterative reconstruction (HIR) of chest ultra-low-dose CT (ULDCT).
BACKGROUND: The risks and prognosis of mild intracerebral hemorrhage (ICH) patients were easily overlooked by clinicians. Our goal was to use machine learning (ML) methods to predict mild ICH patients' neurological deterioration (ND) and 90-day progn...
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