Results 141 to 150 of about 211,599 (259)
Dynamic Thermography-Based Early Breast Cancer Detection Using Multivariate Time Series. [PDF]
Espejel-Rivera MA +3 more
europepmc +1 more source
ABSTRACT Background Surgical site infection (SSI) is a major complication after ileal pouch–anal anastomosis (IPAA) in pediatric ulcerative colitis (UC), significantly impairing quality of life. The lymphocyte‐to–C‐reactive protein ratio (LCR), a composite marker of systemic inflammation and immune/nutritional status, has emerged as a potential ...
Yuhki Koike +9 more
wiley +1 more source
An Outlier Suppression and Adversarial Learning Model for Anomaly Detection in Multivariate Time Series. [PDF]
Zhang W, Li T, He P, Yang Y, Wang S.
europepmc +1 more source
In this retrospective study of 289 patients with Crohn's disease undergoing a single‐incision laparoscopy‐first (SILS‐first) strategy, conversion to open surgery was required in only 11.8% of cases. Fistula formation, colon resection, and smoking history were identified as independent risk factors for conversion, while postoperative complications and ...
Yuki Horio +9 more
wiley +1 more source
Medical irregular multivariate time series forecasting based on multi-scale temporal-frequency domain patch fusion and dynamic graph. [PDF]
Liu X, Gong T, Li Y, Li N, Ding S.
europepmc +1 more source
Flexible tactile sensors have considerable potential for broad application in healthcare monitoring, human–machine interfaces, and bioinspired robotics. This review explores recent progress in device design, performance optimization, and intelligent applications. It highlights how AI algorithms enhance environmental adaptability and perception accuracy
Siyuan Wang +3 more
wiley +1 more source
A multivariate time series prediction model based on the KAN network. [PDF]
Long Y, Qin X.
europepmc +1 more source
Heat generation in lithium‐ion batteries affects performance, aging, and safety, requiring accurate thermal modeling. Traditional methods face efficiency and adaptability challenges. This article reviews machine learning‐based and hybrid modeling approaches, integrating data and physics to improve parameter estimation and temperature prediction ...
Qi Lin +4 more
wiley +1 more source
Improving Multivariate Time-Series Anomaly Detection in Industrial Sensor Networks Using Entropy-Based Feature Aggregation. [PDF]
Wang B.
europepmc +1 more source
Accelerating Biosensor Discovery: A Computationally‐Driven Pipeline for Microplastics Monitoring
A computationally guided pipeline unites molecular simulation, synthetic biology, electrochemical engineering, and machine learning to accelerate biosensor discovery. A Bacillus anthracis carbohydrate‐binding module is used to develop a high‐performance micro‐ and nanoplastics sensor with greatly reduced error and variability.
Gabriel X. Pereira +13 more
wiley +1 more source

