BACKGROUND: Large language models (LLMs) have great potential to improve and make the work of clinicians more efficient. Previous studies have mainly focused on web-based services, such as ChatGPT, often with simulated cases. For the processing of pe...
OBJECTIVE: To develop, validate, and compare a Traditional Multivariable Logistic Regression model with a Machine Learning-based LASSO Regression Model for predicting significant renal function recovery in adult patients undergoing surgical repair fo...
With the advancement of deep learning technologies, more and more researchers have begun developing end-to-end automatic sleep stage classification frameworks. However, these frameworks typically require access to large electroencephalogram (EEG) dat...
Machine learning models are increasingly applied to assisted reproductive technologies (ART), yet most studies rely on conventional algorithms with limited optimization. This proof-of-concept study investigates whether a hybrid Logistic Regression-Ar...
Globally, road traffic accidents (RTAs) remain a major cause of death, particularly among individuals aged 15-30 years. While Sweden has been at the forefront of traffic safety through the Vision Zero initiative, in-hospital management remains crucia...
Diabetic retinopathy (DR) is a leading cause of preventable vision loss. While DR screening is critical, evidence on the reach and implementation of different screening models in primary healthcare settings is limited. This study evaluated the reach ...
Artificial intelligence (AI) tools like ChatGPT-4o are increasingly utilized in prenatal care. However, their reliability and clinical applicability for healthcare providers in first-trimester screening remain unclear. This study aimed to evaluate th...
Inflammatory bowel disease (IBD), including Crohn's disease and Ulcerative colitis, often shows variable responses to biological therapies. Identifying the most significant variables for predicting the response to these therapies could help prioritiz...
The combination of sports psychology and new wearable technology is allowing experts to assess psychological and cognitive performance in elite basketball more accurately. This study investigates the application of Human Activity Recognition (HAR) us...
Prediabetes is a major risk factor for the development of diabetes, defined by blood glucose levels that are elevated but not yet high enough to meet the diagnostic criteria for Diabetes Mellitus. This condition is often clinically "silent" yet it ca...
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