Results 221 to 230 of about 150,441 (331)

Decoding temporal miRNA signatures of semen under in vitro exposure for forensic time since deposition estimation using machine learning‐driven modeling

Interdisciplinary Medicine, EarlyView.
This study develops a novel miRNA‐based framework for estimating the time since deposition of semen stains, combining small RNA sequencing with machine learning. Time‐dependent miRNA modules were identified using Mfuzz clustering and WGCNA, followed by a multi‐stage feature selection pipeline that reduced 261 candidate miRNAs to a minimal 7‐miRNA panel.
Meiming Cai, Qiong Lan, Tong Xie, Qinglin Liu, Ming Zhao, Xiaolian Wu, Xin Shi, Ruonan Shen, Yiman Wu, Chen Mao, Bin Cong, Bofeng Zhu   +11 more
wiley   +1 more source

Development and validation of a multifactorial risk prediction model for breast cancer patients with co-occurring thyroid cancer: a retrospective matched case-control study. [PDF]

Front Oncol
Yin J, Guo Z, Yi W, He Y, Luo Y, Zhu K, Yuan S, Du G.   +7 more
europepmc   +1 more source

Magnetocardiography combined with machine learning for pulmonary hypertension detection and improved short‐term risk assessment

Interdisciplinary Medicine, EarlyView.
Magnetocardiography (MCG) enables non‐invasive mapping of cardiac magnetic fields. In this study, an MCG‐based machine learning model detects pulmonary hypertension with robust performance. Furthermore, MCG features may improve the accuracy of short‐term risk assessment.
Yuankun Qi, Jiaqi Liang, Kai Ma, Xiaoyu Hu, Yu Zhang, Xiaole Han, Dong Xu, Xu Zhang, Xiaopei Cui, Min Xiang, Hongyu Zhang, Jiancheng Fang   +11 more
wiley   +1 more source

Comparative evaluation of several models for forecasting hourly electricity use in a steel plant. [PDF]

Sci Rep
Gu F, Zhao Y.
europepmc   +1 more source

Machine Learning‐Based Estimation of Reference Evapotranspiration and Crop Coefficients for Wheat Under Diverse Climatic Conditions

Irrigation and Drainage, EarlyView.
ABSTRACT Accurate estimation of reference evapotranspiration (ET0) and crop coefficients (Kc) is critical for irrigation planning, particularly in data‐limited regions where agriculture dominates freshwater consumption. Although machine learning (ML) methods have been widely applied to ET0 and Kc estimation, most studies address these parameters ...
Ilker Angin, Hasan Er, Mete Yaganoglu, Muhammed Sungur Demir, Abdullah Muratoglu   +4 more
wiley   +1 more source

A multimodal mutual information‐guided feature selection framework for predicting rehabilitation response in Parkinson's disease with postural instability and gait disorder

Journal of Intelligent Medicine, EarlyView.
A mutual information–guided sequential forward selection framework applied to multimodal baseline data identified key EEG and MRI features, which showed robust predictive performance across multiple machine learning models. Abstract Postural instability and gait disorder (PIGD) subtype of Parkinson's disease (PD) is marked by heterogeneous motor and ...
Yu Shi, Hongbo Zhao, Deyu Wang, Jun Pang, Hanna Lu, Xiaodong Zhu, Lin Meng   +6 more
wiley   +1 more source

Leveraging machine learning for accurate forecasting of pulmonary tuberculosis epidemics in a coastal city in China. [PDF]

Trop Med Health
Yang J, Pan J, Chen J, Xu Y, Zhang X.
europepmc   +1 more source

Molecular descriptor driven QSPR modeling of Papp, TEER and Efflux Ratio from Caco‐2 cells using machine learning for various phytochemicals

Journal of the Science of Food and Agriculture, EarlyView.
Abstract BACKGROUND The present study aimed to develop and validate quantitative structure–property relationship (QSPR) models for predicting permeability related bioavailability indicators including apparent permeability (Papp), trans‐epithelial electrical resistance (TEER) and efflux ratio (ER) based on molecular descriptors (n = 5003) of 83 ...
Jin‐Woo Kim, Rixing Cong, Jin‐Soo Park, Keunwan Park, Kyungsu Kang, Soon‐Mi Shim   +5 more
wiley   +1 more source

Enhancing credit card fraud detection with a hybrid approach using machine and deep learning. [PDF]

Sci Rep
Gamal N, Younis EMG, Makram WM.
europepmc   +1 more source

Exploration of a Multimodal Machine Learning Model Integrating Ultrasound and Clinical Indicators for the Diagnosis of Diabetic Peripheral Neuropathy

Journal of Ultrasound in Medicine, EarlyView.
Objectives Based on ultrasound technology and clinical indicators, this study intends to develop multiple risk prediction models for diabetic peripheral neuropathy (DPN), conduct comparative analyses of these models, and further evaluate and validate the diagnostic efficacy of the optimal model for DPN as well as its potential in clinical application ...
Bo‐yu She, Meng‐lu Song, Wen‐bin Chen, Kun‐bin Wu, Zhen‐han Lai   +4 more
wiley   +1 more source