BACKGROUND: Metabolic syndrome (MetS) is characterized by chronic inflammation and can be worsened by circadian disruption, which is common among shift work. Machine learning can predict the risk of MetS in shift workers using inflammatory biomarkers...
Journal of chemical information and modeling
Dec 27, 2025
This study integrates principal component analysis (PCA) with random forest (RF) modeling to present an enhanced machine learning framework for predicting gas-phase vacuum ultraviolet/ultraviolet (VUV/UV) absorption spectra. This method overcomes a s...
Computer assisted surgery (Abingdon, England)
Dec 26, 2025
Reinforcement learning (RL) has emerged as a powerful artificial intelligence paradigm in medical image analysis, excelling in complex decision-making tasks. This systematic review synthesizes the applications of RL across diverse imaging domains-inc...
Early diagnosis significantly improves survival rates for hepatocellular carcinoma (HCC), yet traditional methods face limitations, including specialized instruments/personnel and prolonged reporting cycles. While lateral flow immunoassay (LFA) offer...
Environmental processes including ballasted flocculation (BF) present significant optimization challenges due to complex multicomponent interactions and small, heterogeneous experimental data sets that frequently lead to overfitted machine learning (...
Journal of chemical information and modeling
Dec 26, 2025
Accurate prediction of molecular properties is essential for computational design in many areas of chemistry. Deep learning has been used in these prediction tasks for a wide variety of molecular properties, and the availability of user-friendly open...
Journal of gastrointestinal and liver diseases : JGLD
Dec 26, 2025
BACKGROUND AND AIMS: Differential diagnosis between irritable bowel syndrome (IBS) and inflammatory bowel disease (IBD) represents a major challenge in modern gastroenterology due to overlapping symptoms, limitations of traditional diagnostic methods...
This study systematically investigates the alterations in electroencephalogram (EEG) microstates in patients with refractory epilepsy(RE) across different seizure stages. A novel EEG microstate analysis framework is proposed to address the limitation...
Cerebral arteriovenous malformation (AVM) is a cerebrovascular disease associated with a risk of intracranial hemorrhage. Currently, most risk prediction models for AVM rupture are based on demographic characteristics and lesion morphology, while qua...
Coronary heart disease (CHD) remains the leading cause of mortality worldwide, disproportionately affecting low- and middle-income countries where diagnostic resources are limited. Traditional statistical models often fail to deliver adequate predict...
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