The proliferation, metastasis, and drug resistance of cancer cells pose significant challenges to the treatment of lung squamous cell carcinoma (LUSC). However, there is a lack of optimal predictive models that can accurately forecast patient prognos...
PURPOSE: This meta-analysis aimed to evaluate the performance of machine learning (ML) models in predicting postoperative delirium (POD) and to provide guidance for clinical application.
The proliferation of omics data has advanced cancer biomarker discovery but often falls short in external validation, mainly due to a narrow focus on prediction accuracy that neglects clinical utility and validation feasibility. We introduce three- a...
BACKGROUND: Hepatocellular carcinoma (HCC) poses a significant global health challenge due to its poor prognosis and limited therapeutic modalities. Anoikis and ErbB signaling pathways are pivotal in cancer cell proliferation and metastasis, but thei...
UNLABELLED: Epilepsy stands as one of the prevalent and significant neurological disorders, representing a critical healthcare challenge. Recently, machine learning techniques have emerged as versatile tools across various healthcare domains, encompa...
Digestive and liver disease : official journal of the Italian Society of Gastroenterology and the Italian Association for the Study of the Liver
Oct 8, 2024
BACKGROUND: The presence of acute kidney injury (AKI) significantly increases in-hospital mortality risk for cirrhotic patients. Early prognosis prediction for these patients is crucial. We aimed to develop and validate a machine learning model for i...
Annals of the New York Academy of Sciences
Oct 8, 2024
Atrial fibrillation (AF) is a severe condition associated with high morbidity and mortality, including an increased risk of stroke and poor outcomes poststroke. Our understanding of the prognosis in AF remains poor. Machine learning (ML) has been app...
Although in vitro fertilization (IVF) has become an extremely effective treatment option for infertility, there is significant underutilization of IVF by patients who could benefit from such treatment. In order for patients to choose to consider IVF ...
INTRODUCTION: Non-alcoholic fatty liver disease (NAFLD) represents a major global health challenge, often undiagnosed because of suboptimal screening tools. Advances in machine learning (ML) offer potential improvements in predictive diagnostics, lev...
BACKGROUND: Despite advances in neuro-oncology, treatments of glioma and tools for predicting the outcome of patients remain limited. The objective of this research is to construct a prognostic model for glioma using the Homologous Recombination Defi...