This study aims to use machine learning methods to examine the causative factors of significant crashes, focusing on accident type and driver's age. In this study, a wide-ranging data set from Jeddah city is employed to look into various factors, suc...
PURPOSE: Early onset scoliosis (EOS) patient diversity makes outcome prediction challenging. Machine learning offers an innovative approach to analyze patient data and predict results, including LOS in pediatric spinal deformity surgery.
PURPOSE: This study aimed to develop machine learning algorithms for identifying predictive factors associated with the risk of postoperative surgical site infection in patients with lower extremity fractures.
BACKGROUND: Type 2 Diabetes Mellitus (T2DM) presents a significant healthcare challenge, with considerable economic ramifications. While blood glucose management and long-term metabolic target setting for home care and outpatient treatment follow est...
OBJECTIVES: To predict the dental caries outcomes in young adults from a set of longitudinally-obtained predictor variables and identify the most important predictors using machine learning techniques.
Chain reaction crashes (CRC) begin with a two-vehicle collision and rapidly intensify as more vehicles get directly involved. CRCs result in more extensive damage compared to two-vehicle crashes and understanding the progression of a two-vehicle coll...
BMC medical informatics and decision making
May 2, 2024
BACKGROUND: Machine learning (ML) classifiers are increasingly used for predicting cardiovascular disease (CVD) and related risk factors using omics data, although these outcomes often exhibit categorical nature and class imbalances. However, little ...
BACKGROUND: Postoperative ileus (POI) continues to be a major cause of morbidity following colorectal surgery. Despite best efforts, the incidence of POI in colorectal surgery remains high (~30%). This study aimed to investigate machine learning tech...
BACKGROUND: Prediction of drug-induced long QT syndrome (diLQTS) is of critical importance given its association with torsades de pointes. There is no reliable method for the outpatient prediction of diLQTS.
International journal of surgery (London, England)
May 1, 2024
BACKGROUND: Early identification of patients at high-risk of postoperative acute kidney injury (AKI) can facilitate the development of preventive approaches. This study aimed to develop prediction models for postoperative AKI in noncardiac surgery us...