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Estimating oxygen uptake in simulated team sports using machine learning models and wearable sensor data: A pilot study.
PloS one
Apr 21, 2025
Accurate assessment of training status in team sports is crucial for optimising performance and reducing injury risk. This pilot study investigates the feasibility of using machine learning (ML) models to estimate oxygen uptake (VO2) with wearable se...
Artificial intelligence prediction model for readmission after DIEP flap breast reconstruction based on NSQIP data.
Journal of plastic, reconstructive & aesthetic surgery : JPRAS
Apr 20, 2025
BACKGROUND: Readmissions following deep inferior epigastric perforator (DIEP) flap breast reconstruction represent a significant healthcare burden, yet current risk prediction methods lack precision in identifying high-risk patients. We developed a m...
Machine-learning guided differentiation between photoplethysmography waveforms of supraventricular and ventricular origin.
Computer methods and programs in biomedicine
Apr 20, 2025
BACKGROUND: It is unclear, whether photoplethysmography (PPG) waveforms from wearable devices can differentiate between supraventricular and ventricular arrhythmias. We assessed, whether a neural network-based classifier can distinguish the origin of...
A Deep Learning Survival Model for Evaluating the Survival Prognosis of Papillary Thyroid Cancer: A Population-Based Cohort Study.
Annals of surgical oncology
Apr 20, 2025
BACKGROUND: Deep learning can assess the individual survival prognosis in sizeable datasets with intricate underlying processes. However, studies exploring the performance of deep learning survival in papillary thyroid cancer (PTC) are lacking. This ...
X-ray based radiomics machine learning models for predicting collapse of early-stage osteonecrosis of femoral head.
Scientific reports
Apr 20, 2025
This study aimed to develop an X-ray radiomics model for predicting collapse of early-stage osteonecrosis of the femoral head (ONFH). A total of 87 patients (111 hips; training set: n = 67, test set: n = 44) with non-traumatic ONFH at Association Res...
Interpretable machine learning model for prediction functional cure in chronic hepatitis B patients receiving Peg-IFN therapy: A multi-center study.
International journal of medical informatics
Apr 19, 2025
BACKGROUND: Functional cure is the ideal treatment goal for chronic hepatitis B (CHB) treatment. We developed and validated machine learning (ML) models to predict functional cure in CHB patients.
Impact of using an AI scribe on clinical documentation and clinician-patient interactions in allied health private practice: perspectives of clinicians and patients.
Musculoskeletal science & practice
Apr 19, 2025
BACKGROUND: The burden associated with clinical documentation can negatively impact patient care and job satisfaction amongst allied health professionals (AHPs). Digital scribes based on artificial intelligence (AI) may address these issues, but this...
Performance of the artificial intelligence-based Swiss medical assessment system versus Manchester triage system in the emergency department: A retrospective analysis.
The American journal of emergency medicine
Apr 19, 2025
BACKGROUND: The emergence of artificial intelligence (AI) offers new opportunities for applications in emergency medicine, including patient triage. This study evaluates the performance of the Swiss Medical Assessment System (SMASS), an AI-based deci...
Dose-response association between OGTT and adverse perinatal outcomes after IVF treatment: A cohort study based on a twin population.
Journal of endocrinological investigation
Apr 19, 2025
BACKGROUND: Investigate the association between Oral Glucose Tolerance Test (OGTT) after in vitro fertilization (IVF) treatment and adverse maternal and neonatal outcomes in twin pregnancies.
Identification and validation of a novel machine learning model for predicting severe pelvic endometriosis: A retrospective study.
Scientific reports
Apr 19, 2025
This study aimed to explore potential risk factors for severe endometriosis and to develop a model to predict the risk of severe endometriosis. A total of 308 patients with endometriosis were analyzed. Least absolute shrinkage and selection operator ...
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