The process of aging and metabolism is intimately intertwined; thus, developing biomarkers related to metabolism is critical for delaying aging. However, few studies have identified reliable markers that reflect aging trajectories based on machine le...
The prediction of poor ovarian response (POR) for stratified interference is a critical clinical issue that has received an increasing amount of recent concern. Anthropogenic diagnostic modes remain too simple for the handling of actual clinical comp...
Premature all-cause mortality is high in patients receiving peritoneal dialysis (PD). The accurate and early prediction of mortality is critical and difficult. Three prediction models, the logistic regression (LR) model, artificial neural network (AN...
BACKGROUND: Early diagnosis of severe acute pancreatitis (SAP) is essential to minimize its mortality and improve prognosis. We aimed to develop an accurate and applicable machine learning predictive model based on routine clinical testing results fo...
We developed and validated a new prognostic model for predicting the overall survival in clear cell renal cell carcinoma (ccRCC) patients. In this study, artificial intelligence (AI) algorithms including random forest and neural network were trained ...
Despite the increasing incidence and high morbidity associated with dementia, a simple, non-invasive, and inexpensive method of screening for dementia is yet to be discovered. This study aimed to examine whether artificial intelligence (AI) could dis...
Aging is emerging as a druggable target with growing interest from academia, industry and investors. New technologies such as artificial intelligence and advanced screening techniques, as well as a strong influence from the industry sector may lead t...
Heart failure is a global health problem that affects approximately 26 million people worldwide. As conventional diagnostic techniques for heart failure have been in practice with various limitations, it is necessary to develop novel diagnostic model...
The composition and relative abundances of immune cells in the tumor microenvironment are key factors affecting the progression of lung adenocarcinomas (LUADs) and the efficacy of immunotherapy. Using the cancer gene expression dataset from The Cance...
Aging clocks that accurately predict human age based on various biodata types are among the most important recent advances in biogerontology. Since 2016 multiple deep learning solutions have been created to interpret facial photos, omics data, and cl...