OBJECTIVE: Due to the high global prevalence of silicosis and the ongoing challenges in its diagnosis, this pilot study aims to screen biomarkers from routine blood parameters and develop a multi-biomarker model for its early detection.
OBJECTIVE: To analyze the influencing factors of early-onset preeclampsia (EOPE). And to construct and validate the prediction model of EOPE using machine learning algorithm.
BACKGROUND: Cancer patients have up to a 3-fold higher risk for cardiovascular disease (CVD) than the general population. Traditional CVD risk scores may be less accurate for them. We aimed to develop cancer-specific CVD risk scores and compare them ...
BACKGROUND: Assessing the relative performance of machine learning (ML) methods and conventional statistical methods in predicting prognosis in heart failure (HF) still remains a challenging research field.
OBJECTIVES: Alzheimer's disease (AD) poses a significant challenge for individuals aged 65 and older, being the most prevalent form of dementia. Although existing AD risk prediction tools demonstrate high accuracy, their complexity and limited access...
Journal of health, population, and nutrition
39920736
BACKGROUND: Diabetes mellitus, an endocrine system disease, is a common disease involving many patients worldwide. Many studies are performed to evaluate the correlation between micronutrients/macronutrients on diabetes but few of them have a high st...
In prostate cancer (PCa), risk calculators have been proposed, relying on clinical parameters and magnetic resonance imaging (MRI) enable early prediction of clinically significant cancer (CsPCa). The prostate imaging-reporting and data system (PI-RA...
Decision-making in chronic diseases guided by clinical decision support systems that use models including multiple variables based on artificial intelligence requires scientific validation in different populations to optimize the use of limited human...
European journal of pain (London, England)
39902807
BACKGROUND: Recurrence is common in chronic low back pain (CLBP). However, predicting the recurrence risk remains a challenge. The aim is to develop and validate a machine learning tool to predict the recurrence risk in patients with CLBP by using mu...
Biomarkers : biochemical indicators of exposure, response, and susceptibility to chemicals
39899375
BACKGROUND AND OBJECTIVES: Prior studies have shown that small non-coding RNAs (sncRNAs) are associated with cancer occurrence or development. Recently, a newly discovered class of small ncRNAs known as PIWI-interacting RNAs (piRNAs) have been found ...