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...
Non-Suicidal Self-Injury (NSSI) is a prevalent and complex behavior among adolescents, often linked to negative emotions such as loneliness, anxiety, and emptiness. Traditional self-report and experimental methods rely on autobiographical recall and ...
BACKGROUND: Lung adenocarcinoma (LUAC) patients with micropapillary (MP) and/or solid (S) generally demonstrate a poorer survival prognosis. In the diagnosis and treatment of stage IA LUAC, precisely establishing personalized treatment strategies for...
OBJECTIVE: To construct and validate a predictive model for the risk of postoperative constipation in middle-aged and elderly patients with lower limb fractures based on machine learning algorithms, so as to provide decision-making support for clinic...
BACKGROUND: Spontaneous preterm birth (sPTB) remains a major cause of neonatal morbidity and early risk assessment was poor. This study aimed to evaluate the association and predictive potential of serum biomarkers and maternal factors with sPTB.
Early detection of knee osteoarthritis (KOA) is essential to improve treatment outcomes and reduce its long-term impact. However, early diagnosis of KOA (EKOA) remains difficult due to the absence of standardised criteria and the subtle or intermitte...
Patients with early-onset kidney cancer (EOKC) face a marked decline in prognosis after distant metastasis, yet the accuracy of current predictive methods remains limited. This study aims to develop a predictive model using multiple machine learning ...
The European journal of general practice
Nov 17, 2025
BACKGROUND: Healthcare demand in English general practice exceeds supply, necessitating practice efficiency. To our knowledge, no study has explored factors associated with practice efficiency in England using a quality-adjusted output.
OBJECTIVES: To develop and compare prediction models for 30-day and 1-year mortality in Heart failure with preserved ejection fraction (HFpEF) using EHR data, utilizing both traditional and machine learning (ML) techniques.
Pediatric fungemia in pediatric intensive care units (PICUs) carries high mortality. We evaluated whether the Candida Score, combined with clinical variables, predicts mortality after diagnosis using a prespecified multivariable logistic regression (...
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