Associations of Sleep and Shift Work with Osteoarthritis Risk
Objective Daily rhythms may be critical for maintaining homeostasis of joint tissues. We aimed to investigate the relationships between circadian clock disruption, sleep, and osteoarthritis (OA) risk in humans. Methods In the UK Biobank, a prospective 500,000‐person cohort, we evaluated associations between sleep duration, sleeplessness/insomnia, and ...
Elizabeth L. Yanik +5 more
wiley +1 more source
Modeling thermoelectric performance of p-type Cu3SbSe4-based chalcogenide materials using decision trees and structural risk error minimization intelligent computational methods. [PDF]
Alharbi FS.
europepmc +1 more source
Objective Somatic items used in depression assessments can potentially overlap with symptoms related to physical illness, including systemic sclerosis (SSc). No studies have looked at whether somatic depression items may be influenced by diffuse versus limited SSc disease subtypes, which are associated with varying degrees of symptom presentation.
Sophie Hu +109 more
wiley +1 more source
Interpretable machine learning model for predicting 5-Year postoperative recurrence risk in patients with stage III colon cancer using preoperative laboratory tests: a two-centre study. [PDF]
Wei H +5 more
europepmc +1 more source
Objective We assessed the effectiveness of PrismRA to improve clinical outcomes among patients with rheumatoid arthritis (RA) initiating treatment with a biologic or targeted synthetic disease‐modifying antirheumatic drug (b/tsDMARD). Methods PrismRA incorporated 19 gene expression features and four clinical features to assess a patient's likelihood of
Fenglong Xie +3 more
wiley +1 more source
Leveraging topological indices and machine learning for advanced prediction of antidepressant drug properties. [PDF]
Zhang G +6 more
europepmc +1 more source
This paper proposes two projector‐based Hopfield neural network (HNN) estimators for online, constrained parameter estimation under time‐varying data, additive disturbances, and slowly drifting physical parameters. The first is a constraint‐aware HNN that enforces linear equalities and inequalities (via slack neurons) and continuously tracks the ...
Miguel Pedro Silva
wiley +1 more source
Development and evaluation of machine learning algorithms for the prediction of opioid-related deaths among UK patients with non-cancer pain. [PDF]
Benitez-Aurioles J +4 more
europepmc +1 more source
Predicting extreme defects in additive manufacturing remains a key challenge limiting its structural reliability. This study proposes a statistical framework that integrates Extreme Value Theory with advanced process indicators to explore defect–process relationships and improve the estimation of critical defect sizes. The approach provides a basis for
Muhammad Muteeb Butt +8 more
wiley +1 more source
Explainable attrition risk scoring for managerial retention decisions in human resource analytics. [PDF]
Pavithran MS, Vadivel SM.
europepmc +1 more source

