Key gene screening and diagnostic model establishment for acute type a aortic dissection by Yue Pan, Zhiming Yu, Xiaoyu Qian, Xuesong Zhang, Qun Xue, Weizhang Xiao

“…Recent studies highlight the role of immune dysregulation, vascular smooth muscle cell (VSMC) apoptosis, and metabolic-epigenetic interactions in AD pathogenesis, underscoring the need for novel biomarkers and therapeutic targets.ObjectiveThis study aims to identify critical genes and molecular pathways associated with ATAAD, develop a multi-omics diagnostic model, and evaluate potential therapeutic interventions to improve clinical outcomes.MethodsTranscriptome datasets from the Gene Expression Omnibus (GEO) database were analyzed using differential expression analysis, weighted gene co-expression network analysis (WGCNA), and machine learning algorithms (SVM, Random Forest, LASSO regression). …”
Get full text

Research on automatic identification method for pipeline girth weld defects based on X-ray images and sparse representation by Shaohui JIA, Yaping LI, Weixin GAO, Yunchao PENG, Xinjian ZHANG, Yuxia WANG

“…Based on Suspected Defect Region (SDR) and formulated gray densities, a clustering-based SDR segmentation algorithm was constructed, aimed at precise segmentation of defect SDRs in various shapes. …”
Get full text

Nonlinear oscillations of a lumped system with series spring, piezoelectric device, and feedback controller by M. K. Abohamer, T. S. Amer, A. A. Galal, Mona A. Darweesh, A. Arab, Taher A. Bahnasy

“…The system is described by differential and algebraic equations, forming a dynamic model governed by differential-algebraic equations (DAE). …”
Get full text

Whole genome resequencing reveals genetic diversity, population structure, and selection signatures in local duck breeds by Pengwei Ren, Yongdong Peng, Liu Yang, Muhammad Zahoor Khan, Yadi Jing, Chao Qi, Zhansheng Liu, Shuer Zhang, Nenzhu Zheng, Meixia Zhang, Xiang Liu, Zhiming Zhu, Mingxia Zhu

“…We also used a random forest model algorithm to identify specific breed-identification SNPs, ensuring accurate differentiation of the three breeds. …”
Get full text

Microcomputed tomography as a diagnostic tool for detection of lymph node metastasis in non-small cell lung cancer: A decision-support approach for pathological examination “A pilo... by Ayten Kayı Cangır, Süleyman Gökalp Güneş, Kaan Orhan, Hilal Özakıncı, Yusuf Kahya, Duru Karasoy, Serpil Dizbay Sak

“…The employment of micro-computed tomography (micro-CT) facilitates a three-dimensional (3D) evaluation of all LNs without compromising sample integrity. …”
Get full text

Identifying the risk of Kawasaki disease based solely on routine blood test features through novel construction of machine learning models by Tzu-Hsien Yang, Ying-Hsien Huang, Yuan-Han Lee, Jie-Nan Lai, Kuang-Den Chen, Mindy Ming-Huey Guo, Yan Pan, Chun-Yu Chen, Wei-Sheng Wu, Ho-Chang Kuo

“…KDpredictor leverages only the routine blood test features, including complete blood count with differential count, C-reactive protein, and alanine aminotransferase. …”
Get full text

Long-term follow-up of patients with arterial hypertension and ischemic stroke by V. B. Simonenko, E. A. Shirokov, Yu. V. Ovchinnikov

“…To study the features of arterial hypertension (AH) clinical course predisposing to ischemic stroke (IS) development; to evaluate hemodynamic changes after IS; to develop a clinical algorithm for long-term follow-up and IS prevention in AH patients.Material and methods. …”
Get full text

The Comparison of De Novo Grade 3 Follicular Lymphoma and Transformed Grade 3 Follicular Lymphoma: Own Data by LV Plastinina, AM Kovrigina, TN Obukhova, ES Nesterova, AU Magomedova, YaK Mangasarova, AE Misyurina, FE Babaeva, SM Kulikov, AI Vorob’ev, SK Kravchenko

“…Results. We proposed an algorithm for differential diagnosis of the 2 types of grade 3 FL: de novo FL (n = 22) and transformed FL (n = 21). …”
Get full text

Machine Learning-Driven Transcriptome Analysis of Keratoconus for Predictive Biomarker Identification by Shao-Hsuan Chang, Lung-Kun Yeh, Kuo-Hsuan Hung, Yen-Jung Chiu, Chia-Hsun Hsieh, Chung-Pei Ma

“…Machine learning algorithms were then used to analyze the gene sets, with SHapley Additive exPlanations (SHAP) applied to assess the contribution of key feature genes in the model’s predictions. …”
Get full text

Diagnostic Value of Glycosylated Extracellular Vesicle microRNAs in Gastric Cancer by Wang S, Ma C, Ren Z, Zhang Y, Hao K, Liu C, Xu L, He S, Zhang J

“…The signatures were screened in a discovery cohort of GC patients (n=55) and non-disease controls (n=46) using an integrated process, including high-throughput sequencing technology, screening using a complete bioinformatics algorithm, validation using RT-qPCR, and evaluation by constructing a diagnostic model. …”
Get full text

Understanding the flowering process of litchi through machine learning predictive models by SU Zuanxian, NING Zhenchen, WANG Qing, CHEN Houbin

“…The algorithms (RF and STR) with the smallest Mean Absolute Error (MAE) and the highest residual error (RMSE) and the highest correlation coefficient (RP2) were selected for further parameter optimization and evaluation. …”
Get full text

Machine learning based screening of biomarkers associated with cell death and immunosuppression of multiple life stages sepsis populations by Jie Yang, Fanyan Ou, Binbin Li, Lixiong Zeng, Qiuli Chen, Houyu Gan, Jianing Yu, Qian Guo, Jihua Feng, Jianfeng Zhang

“…The SHAP algorithm was further used to quantify the contribution of each gene based on cell death features to the prediction of sepsis. …”
Get full text

Application of cross-polarization imaging in distinguishing between squamous and columnar epithelium of the cervix by Cat Phan Ngoc Khuong, Hieu Nguyen Trung, Duc Le Huynh, Quynh Nguyen Ngoc, Hai Pham Thanh, Long Nguyen, Hanh Tran Thi Thu, Tu Ly Anh, Tien Tran Van

“…This method significantly increases the contrast between these tissue types, facilitating clearer differentiation and improving diagnostic accuracy. Notably, the combination of the cross-polarization imaging technique with our proposed algorithm enables the clear observation of the SCJ boundary. …”
Get full text

Possibilities of magnet-resonance tomography usage while examining patients with reccurent genital prolapse by Banakhevych R.M.

“…The developed algorithm of dynamic magnetic resonance imaging in patients with recurrent pelvic hernia significantly improves the quality of diagnosis. …”
Get full text

Exploration of heterogeneity of treatment effects across exercise-based interventions for knee osteoarthritis by Paul A. Dennis, Livia Anderson, Cynthia J. Coffman, Sara Webb, Kelli D. Allen

“…Three metalearners with three machine learning algorithms each and a simple interpretable model-based regression tree were used to identify subgroups with differential treatment effects. …”
Get full text

Identification of biomarkers for the diagnosis of type 2 diabetes mellitus with metabolic associated fatty liver disease by bioinformatics analysis and experimental validation by Guiling Wu, Guiling Wu, Sihui Wu, Sihui Wu, Tian Xiong, Tian Xiong, Tian Xiong, You Yao, You Yao, Yu Qiu, Yu Qiu, Yu Qiu, Liheng Meng, Cuihong Chen, Xi Yang, Xi Yang, Xi Yang, Xinghuan Liang, Yingfen Qin

“…Candidate biomarkers were screened using machine learning algorithms combined with 12 cytoHubba algorithms, and a diagnostic model for T2DM-related MAFLD was constructed and evaluated.The CIBERSORT method was used to investigate immune cell infiltration in MAFLD and the immunological significance of central genes. …”
Get full text

Thermographic Data Processing and Feature Extraction Approaches for Machine Learning-Based Defect Detection by Alexey Moskovchenko, Michal Svantner

“…This study focuses on automating the detection of impact damage in carbon fiber-reinforced polymer materials using flash-pulse thermography and ML algorithms. Various machine learning models and data pre-processing techniques were evaluated for their effectiveness in detecting and locating impact damage. …”
Get full text

Exploring T-cell metabolism in tuberculosis: development of a diagnostic model using metabolic genes by Shoupeng Ding, Chunxiao Huang, Jinghua Gao, Chun Bi, Yuyang Zhou, Zihan Cai

“…We identified T-cell-associated metabolic differentially expressed genes (TCM–DEGs) through integrated differential expression analysis and machine learning algorithms (XGBoost, SVM–RFE, and Boruta). …”
Get full text

Estimation of potato leaf area index based on spectral information and Haralick textures from UAV hyperspectral images by Jiejie Fan, Jiejie Fan, Yang Liu, Yang Liu, Yiguang Fan, Yihan Yao, Riqiang Chen, Mingbo Bian, Yanpeng Ma, Huifang Wang, Haikuan Feng, Haikuan Feng, Haikuan Feng

“…The Leaf Area Index (LAI) is a crucial parameter for evaluating crop growth and informing fertilization management in agricultural fields. …”
Get full text

Ultrasonic radiomics in predicting pathologic type for thyroid cancer: a preliminary study using radiomics features for predicting medullary thyroid carcinoma by Dai Zhang, Dai Zhang, Dai Zhang, Dai Zhang, Fan Yang, Fan Yang, Fan Yang, Fan Yang, Wenjing Hou, Wenjing Hou, Wenjing Hou, Wenjing Hou, Ying Wang, Ying Wang, Ying Wang, Ying Wang, Jiali Mu, Jiali Mu, Jiali Mu, Jiali Mu, Hailing Wang, Hailing Wang, Hailing Wang, Hailing Wang, Xi Wei, Xi Wei, Xi Wei, Xi Wei

Get full text