Results 221 to 230 of about 5,693,469 (294)

Development of a Machine Learning Algorithm for Differential Diagnosis Between Primary Immune Thrombocytopenia and Connective Tissue Disease‐Related Thrombocytopenia in Pediatric Patients

Journal of Clinical Laboratory Analysis, EarlyView.
Primary immune thrombocytopenia (ITP) and connective tissue disease‐related thrombocytopenia (CTD‐TP) share overlapping initial presentations in children, often leading to delayed diagnosis and suboptimal management. While existing literature focuses on therapeutic strategies, this study is the first to develop a machine learning (ML)‐based diagnostic ...
Furong Kang, Mei Yan, Yingbin Yue, Xuemei Wang, Yu Liu   +4 more
wiley   +1 more source

Explainable artificial intelligence reveals key surgical parameters in robot-assisted and open radical prostatectomy. [PDF]

Sci Rep
Klein CR, Heuser P, Trunz E, Kristiansen G, Brossart P, Ritter M, Krausewitz P.   +6 more
europepmc   +1 more source

Artificial intelligence‐assisted nanozyme design for medical and environmental applications

Journal of Intelligent Medicine, EarlyView.
AI‐assisted nanozyme design integrates cross‐source data and machine learning to enable predictive structure‐activity relationships, accelerating intelligent diagnostics, precision therapeutics, and environmental surveillance. Abstract Nanozymes, a class of nanomaterials with intrinsic enzyme‐like catalytic activities, have emerged as promising ...
Xiaolin Guo, Hao Zhang, Zihan Zhao, Qingshan Liu, Jiayi Liu, Jiang Huang, Changlong Liu, Xiaoyu Mu   +7 more
wiley   +1 more source

Explainable Deep Learning of Transcriptomes Prioritizes Candidate Biomarkers With Preferential Performance in Gastric Cardia Cancer Cohorts. [PDF]

FASEB J
Xu J, Li C.
europepmc   +1 more source

Early prediction of acute kidney injury in traumatic and non‐traumatic rhabdomyolysis using an interpretable machine learning model: A multicenter study with external validation

Journal of Intelligent Medicine, EarlyView.
Abstract Acute kidney injury (AKI) is a common and severe complication of rhabdomyolysis (RM), and early risk stratification remains challenging because of its multifactorial and heterogeneous nature. We developed and externally validated an interpretable machine learning (ML) model for early prediction of AKI in RM across traumatic and non‐traumatic ...
Chunli Liu, Jie Shi, Fengjuan Wang, Liang Ma, Huangang Hu, Li Zhang, Jie Song, Heng Jin, Dingwei Yang, Xiaoqin Guo, Haojun Fan, Qi Lv   +11 more
wiley   +1 more source

Data-driven trial design: use of target trial emulation to evaluate eligibility criteria in asthma and COPD. [PDF]

Front Med (Lausanne)
Makgoeng SB, Gamalo M, Russo LJ, Pradhan V, Bhattacharjee A, Bhosale N.   +5 more
europepmc   +1 more source

Spatio‐Temporal Analysis of Human Thermal Comfort and Relationships With Large‐Scale Climate Indices Along Ghana's Coastal‐Urban Corridor From 1980 to 2020

International Journal of Climatology, EarlyView.
Four decades of UTCI data show increasing thermal stress along Ghana's coastal‐urban corridor, with very strong heat‐stress days rising by about 1.4 days/year. Random Forest–SHAP analysis with temporal validation identified AOD as the strongest model‐based predictor of monthly UTCI variability, followed by TSA, WHWP, and AMO.
Kwadwo Frimpong, Layin Zhu, Kathleen Baker, Israel Orimoloye   +3 more
wiley   +1 more source

Interpretable machine learning integrating intra-/peritumoral CT radiomics and serum indicators for predicting poorly differentiated esophageal squamous cell carcinoma. [PDF]

Front Oncol
Chen J, He J, Zhang X, Tang X, Yang M, Wang F.   +5 more
europepmc   +1 more source