Rock fracture type recognition based on deep feature learning of microseismic signals by LI Dianze, XU Huajie, ZHANG Bo

“…To enhance feature extraction efficiency, an improved DenseNet model (SE-MPDenseNet) was developed by incorporating multi-feature parallel dense blocks (MP-DenseBlock) and squeeze-and-excitation transition layers (SE-TransLayer). …”
Get full text

AI-driven precision diagnosis and treatment in Parkinson’s disease: a comprehensive review and experimental analysis by Bhekisipho Twala

“…The integration of multiple data modalities and advanced machine learning algorithms enables earlier detection, more accurate monitoring, and optimized therapeutic interventions. …”
Get full text

Landslide susceptibility evaluation considering the importance selection of influencing factors and soil moisture content by Zhongyu WANG, Sumin LI, Liwei YUAN, Weipeng LE

“…The landslide susceptibility in the Fumin County was evaluated using LightGBM and Random Forest models, before and after factor importance selection. …”
Get full text

Revolutionizing Holy-Basil Cultivation With AI-Enabled Hydroponics System by G. Lakshmi Priya, Chanthini Baskar, Sanket Sandeep Deshmane, C. Adithya, Souranil Das

Get full text

Joint Tomek Links (JTL): An Innovative Approach to Noise Reduction for Enhanced Classification Performance by Goksu Tuysuzoglu, Yunus Dogan, Elife Ozturk Kiyak, Mustafa Ersahin, Bita Ghasemkhani, Kokten Ulas Birant, Derya Birant

Get full text

Diagnostic potential of gut microbiota in Parkinson’s disease by V. A. Petrov, V. M. Alifirova, I. V. Saltykova, I. A. Zhukova, N. G. Zhukova, Yu. B. Dorofeeva, O. P. Ikkert, M. A. Titova, Yu. S. Mironova, A. E. Sazonov, M. R. Karpova

“…These profiles were obtained with amplicon sequencing of bacterial 16S rRNA genes. Classifying models were made using the naive Bayes classifier, the artificial neural network, support vector machine, generalized linear model, and partial least squares regression.As a result we established that an optimal classification by the composition of the gut microbiota on the validation sample (sensitivity 91.30%, specificity 91.67% at 91.49% accuracy) amid patients was demonstrated with a naive Bayes classifier using the representation of the following genera as predictors: Christensenella, Methanobrevibacter, Leuconostoc, Enterococcus, Catabacter, Desulfovibrio, Sphingomonas, Yokenella, Atopobium, Fusicatenibacter, Cloacibacillus, Bulleidia, Acetanaerobacterium, and Staphylococcus.Conclusions. …”
Get full text

Identification of novel ABCB4 variants and genotype-phenotype correlation in progressive familial intrahepatic cholestasis type 3 by Senyan Wang, Qi Liu, Xiaoyan Sun, Wenjuan Wei, Leilei Ding, Xiaofang Zhao

“…The study included statistical analysis of clinical information, genetic analysis, multi-species sequence alignment, protein structure modeling, and pathogenicity assessment. Machine learning techniques were applied to identify genotype-phenotype relationships. …”
Get full text

PneuX-Net: An Enhanced Feature Extraction and Transformation Approach for Pneumonia Detection in X-Ray Images by Kashif Munir, Muhammad Usama Tanveer, Hasan J. Alyamani, Amine Bermak, Atiq Ur Rehman

“…To address this problem, we propose PneuX-Net, an ensemble-based feature extraction framework that integrates multiple machine learning (ML) models Random Forest (RF), Gaussian Naïve Bayes (GNB) and K-Nearest Centroid (KNC). …”
Get full text

Hybrid feature fusion in cervical cancer cytology: a novel dual-module approach framework for lesion detection and classification using radiomics, deep learning, and reproducibilit... by Shurong Niu, Lili Zhang, Lina Wang, Xue Zhang, Erniao Liu

Get full text

Wireless Channel Prediction Using Artificial Intelligence With Imperfect Datasets by Gowhar Javanmardi, Ramiro Samano Robles

“…This paper presents the study of machine learning (ML) algorithms for the prediction of vehicular channels under impairments that arise in realistic implementations. …”
Get full text

SOC Estimation of Lithium-Ion Batteries Utilizing EIS Technology with SHAP–ASO–LightGBM by Panpan Hu, Chun Yin Li, Chi Chung Lee

“…This paper proposes a novel machine learning-based approach for SOC estimation by integrating Electrochemical Impedance Spectroscopy (EIS) with the SHapley Additive exPlanations (SHAP) method, Atom Search Optimization (ASO), and Light Gradient Boosting Machine (LightGBM). …”
Get full text

Spatial Estimation of Soil Organic Matter and Total Nitrogen by Fusing Field Vis–NIR Spectroscopy and Multispectral Remote Sensing Data by Dongyun Xu, Songchao Chen, Yin Zhou, Wenjun Ji, Zhou Shi

Get full text

A Short-Term Wind Speed Forecasting Hybrid Model Based on Empirical Mode Decomposition and Multiple Kernel Learning by Yuanyuan Xu, Genke Yang

“…Extensive experimental results show that, compared with existing machine learning methods, the EMD-MKL model proposed in this paper has better performance in terms of the prediction accuracy evaluation indexes and confidence intervals and shows a better ability to generalize.…”
Get full text

A deep learning strategy for accurate identification of purebred and hybrid pigs across SNP chips by Zipeng Zhang, Zhengwen Fang, Yongwang Du, Yilin He, Changsong Qian, Weijian Ye, Ning Zhang, Jianan Zhang, Xiangdong Ding

Get full text

A case study on canola (Brassica napus L.) potential yield prediction using remote sensing imagery and advanced data analytics by Nitin Rai, Harsh Pathak, Maria Villamil Mahecha, Dennis R. Buckmaster, Yanbo Huang, Paul Overby, Xin Sun

“…These models were trained on the yield maps interpolated using three approaches, based on the ground truth yield data points obtained from a harvester. …”
Get full text

Biological age prediction in schizophrenia using brain MRI, gut microbiome and blood data by Rui Han, Wei Wang, Jianhao Liao, Runlin Peng, Liqin Liang, Wenhao Li, Shixuan Feng, Yuanyuan Huang, Lam Mei Fong, Jing Zhou, Xiaobo Li, Yuping Ning, Fengchun Wu, Kai Wu

“…Feature interpretability analysis of the optimal model elucidated that the substantial contributions of the frontal lobe, the temporal lobe and the fornix were effective for biological age prediction. …”
Get full text

RESEARCH ON MULTI-BODY DYNAMIC SIMULATION OF HUMANOID FOOT TYPE STAIR CLIMBING WHEELCHAIR BASED ON ADAMS by ZHU Hua, YANG Hui, HUANG ZhenLi, GUO ChangJian, YU YiPeng

“…It provides an important basis for reasonable selection of the model and the length of the machine,and provided a theoretical basis for the optimization design of other mechanisms.…”
Get full text

Carbon Dioxide Emission Forecasting Using BiLSTM Network Based on Variational Mode Decomposition and Improved Black-Winged Kite Algorithm by Yueqiao Yang, Shichuang Li, Haijun Liu, Jidong Guo

“…Finally, a comparative analysis with other mainstream machine learning and deep learning models revealed that the BiLSTM model consistently achieved the best predictive performance across all industries. …”
Get full text

Advances in Personalized Cancer Vaccine Development: AI Applications from Neoantigen Discovery to mRNA Formulation by Hyunseung Kong

“…For sequence optimization, deep learning models for codon and UTR design improve protein expression and mRNA stability beyond traditional methods. …”
Get full text

Neural network technologies for forecasting and controlling electricity consumption in energy systems by the genetic method by Nikolay K. Poluyanovich, Oleg V. Kachelaev, Marina N. Dubyago, Talia Hernandez Falcón

“…The authors have developed the neural network models and carried out the study to find the optimal structure of a neural network, and the influence of specified neural networks hyperparameters on the error in predicting power consumption. …”
Get full text