Uncovering glycolysis-driven molecular subtypes in diabetic nephropathy: a WGCNA and machine learning approach for diagnostic precision by Chenglong Fan, Guanglin Yang, Cheng Li, Jiwen Cheng, Shaohua Chen, Hua Mi

“…The hub genes associated with DN and glycolysis-related clusters were identified via weighted gene co-expression network analysis (WGCNA) and machine learning algorithms. Finally, the expression patterns of these hub genes were validated using single-cell sequencing data and quantitative real-time polymerase chain reaction (qRT-PCR). …”
Get full text

Exploring the Influencing Factors of Surface Ozone Variability by Explainable Machine Learning: A Case Study in the Basilicata Region (Southern Italy) by Roberta Valentina Gagliardi, Claudio Andenna

“…In this study, a methodological approach combining both supervised and unsupervised machine learning algorithms (MLAs) with the Shapley additive explanations (SHAP) method was used to understand the key factors behind O₃ variability and to explore the nonlinear relationships linking O₃ to these factors. …”
Get full text

Programmable friction control in 3D printed patterned multi-materials: a flexible design strategy by Xinle Yao, Yuxiong Guo, Mingyang Wang, Yaozhong Lu, Zhibin Lu, Xin Jia, Yu Gao, Xiaolong Wang

“…The explainable ML model (linear regression algorithm) analyzes composite-specific tribological and physicochemical data (100 data) to autonomously design patterning surfaces with programmable friction coefficients, validated experimentally (μ = 0.07 ∼ 0.49). …”
Get full text

Introducing HeliEns: A Novel Hybrid Ensemble Learning Algorithm for Early Diagnosis of <i>Helicobacter pylori</i> Infection by Sultan Noman Qasem

“…Recent advancements in machine learning (ML) and quantum machine learning (QML) offer promising non-invasive alternatives capable of analyzing complex datasets to identify patterns not easily discernible by human analysis. …”
Get full text

An Author Gender Detection Method Using Whale Optimization Algorithm and Artificial Neural Network by Fatemeh Safara, Amin Salih Mohammed, Moayad Yousif Potrus, Saqib Ali, Quan Thanh Tho, Alireza Souri, Fereshteh Janenia, Mehdi Hosseinzadeh

“…Text and writings of people on the Internet have valuable information that can be used to identify the gender of an author. Machine learning and meta-heuristic algorithms are valuable techniques to extract hidden patterns useful for detecting gender of a text. …”
Get full text

Medical Diagnostic Systems Using Artificial Intelligence (AI) Algorithms: Principles and Perspectives by Simarjeet Kaur, Jimmy Singla, Lewis Nkenyereye, Sudan Jha, Deepak Prashar, Gyanendra Prasad Joshi, Shaker El-Sappagh, Md. Saiful Islam, S. M. Riazul Islam

Get full text

Artificial intelligence as a transforming factor in motility disorders–automatic detection of motility patterns in high-resolution anorectal manometry by Miguel Mascarenhas, Francisco Mendes, Joana Mota, Tiago Ribeiro, Pedro Cardoso, Miguel Martins, Maria João Almeida, João Rala Cordeiro, João Ferreira, Guilherme Macedo, Cecilio Santander

“…A dataset of 701 HR-ARM exams from a tertiary center, classified according to London Classification, was used to develop and test multiple machine learning (ML) algorithms. The exams were divided in a training and testing dataset with a 80/20% ratio. …”
Get full text

Identifying network state-based Parkinson’s disease subtypes using clustering and support vector machine models by Benedictor Alexander Nguchu, Benedictor Alexander Nguchu, Yifei Han, Yanming Wang, Peter Shaw

“…The features were specifically the gray matter volume and dopaminergic features of the neostriatum, i.e., the caudate, putamen, and anterior putamen. We use machine learning (ML) algorithms, including Random Forest, Logistic Regression, and Support Vector Machine, to evaluate the diagnostic power of the brain features and network patterns in differentiating the PD subtypes and distinguishing PD from HC. …”
Get full text

An evolution of forensic linguistics: From manual analysis to machine learning – A narrative review by R. Thamizh Mani, Vikram Palimar, Mamatha Shivananda Pai, T.S. Shwetha, M. Nirmal Krishnan

“…This narrative review clarifies three core objectives: (1) tracing the field’s historical trajectory from early manual techniques to computational innovations, (2) systematically comparing the accuracy, efficiency, and reliability of manual versus ML-based approaches, and (3) identifying persistent challenges in ML integration, including algorithmic bias and legal admissibility. By synthesizing 77 studies, the analysis reveals that ML algorithms—notably deep learning and computational stylometry—outperform manual methods in processing large datasets rapidly and identifying subtle linguistic patterns (e.g., authorship attribution accuracy increased by 34 % in ML models). …”
Get full text

Brain Computer Interface using Genetic Algorithm with modified Genome and Phenotype Structures by Rohtash Dhiman, A Anshul

“…In the present paper, an effective novel scheme based upon a synergetic approach employing the Genetic Algorithm (GA), Support Vector Machine and Wavelet packet transform for motor imagery classification and optimal Channel selection is proposed. …”
Get full text

Digits Recognition for Arabic Handwritten through Convolutional Neural Networks, Local Binary Patterns, and Histogram of Oriented Gradients by Bushra Mahdi Hasan, Zahraa Jasim Jaber, Ahmad Adel Habeeb

Get full text

MultiModalGraphSearch: Intelligent Massive-Scale SubGraph Discovery for Multi-Category Financial Pattern Mining by Yaohan Qi

Get full text

A Comparative Study on Association Rule Mining Algorithms on the Hospital Infection Control Dataset by Yahya Asmar Zakur, Seyed Bagher Mirashrafi, Laith Rezouki Flaih

Get full text

Using BERT and ZFNet/ELM optimized by improved Orca optimization algorithm for sentiment analysis by Jun Yang, Jafar Safarzadeh

Get full text

EsoDetect: computational validation and algorithm development of a novel diagnostic and prognostic tool for dysplasia in Barrett’s esophagus by Migla Miskinyte, Benilde Pondeca, José B. Pereira-Leal, Joana Cardoso

“…In evaluating the value of gene expression for diagnosis and prognosis, the analyzed datasets allowed for the ranking of biomarkers, resulting in eighteen diagnostic genes and fifteen prognostic genes that were used for further algorithm development. Ultimately, a linear support vector machine algorithm incorporating ten genes was identified for diagnostic application, while a radial basis function support vector machine algorithm, also utilizing ten genes, was selected for prognostic prediction. …”
Get full text

Unveiling ac4C modification pattern: a prospective target for improving the response to immunotherapeutic strategies in melanoma by Jianlan Liu, Pengpeng Zhang, Chaoqin Wu, Binlin Luo, Xiaojian Cao, Jian Tang

“…We developed and confirmed an excellent acRG-related signature (acRGS) utilizing a comprehensive set of 101 algorithm combinations derived from 10 machine learning algorithms. …”
Get full text

Identification of Leaf Rust-Related Gene Signature in Wheat (Triticum Aestivum L.) Using High-Throughput Sequencing, Network Analysis, and Machine Learning Algorithms by Muhammad Farhan, Muhammad Ikram, Jing-E Sun, San-Wei Yang, Yong Wang

Get full text

The impacts of specific place visitations on theft patterns: a case study in Greater London, UK by Tongxin Chen, Kate Bowers, Tao Cheng

“…We utilised geo big data (mobile phone GPS trajectory records) collected from millions of anonymous users to measure footfalls (counts of visitations) attached to place types on weekdays and weekends. An explainable machine learning approach was applied to analyse the impacts of place visitations on theft levels: the ‘XGBoost’ algorithm trained a high-performance regression model and ‘SHapley Additive exPlanations’ (SHAP) values were measured to identify the contributions of different visitation variables to theft levels at specific spatial and temporal scales. …”
Get full text

Exploring shared pathogenic mechanisms and biomarkers in hepatic fibrosis and inflammatory bowel disease through bioinformatics and machine learning by Shangkun Li, Haoyu Li, Mingran Qi

“…The key diagnostic biomarkers were determined via a protein-protein interaction (PPI) network combined with two machine learning algorithms. The logistic regression model was subsequently developed based on these key genes. …”
Get full text

Secure Biometric Identification Using Orca Predators Algorithm With Deep Learning: Retinal Iris Image Analysis by Louai A. Maghrabi, Mohammed Altwijri, Sami Saeed Binyamin, Fouad Shoie Alallah, Diaa Hamed, Mahmoud Ragab

Get full text