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). …”
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Massive Acquisition of Ultraviolet Color Excess Information from GALEX and UVOT Bands by Dongliang Yang, Mingxu Sun, Biwei Jiang, Wenyuan Cui, Ruoyi Zhang, Luyao Shi, Jiachen Wei

“…By considering the impact of stellar parameters ( T _eff , [Fe/H], and ${\rm{log}}\,g$ ) on intrinsic color indices and utilizing the blue-edge method combined with a random forest algorithm, an empirical relationship between stellar parameters and intrinsic ultraviolet color indices is established. …”
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Inverse Dynamic Parameter Identification for Remote Sensing of Soil Moisture From SMAP Satellite Observations by Runze Zhang, Adam Watts, Mohamad Alipour

“…However, there is no consistent trend in the magnitudes of dynamic <italic>h</italic> and &#x03C9; between different algorithms. Identifying the most effective dynamic <italic>h</italic> and &#x03C9; parameters within the SMAP algorithmic framework necessitates not only selecting an appropriate parameter range but also accurately tracking the temporal evolutions of surface roughness and vegetation scattering. …”
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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. …”
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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. …”
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A comparative study of Mongolian medicine prescriptions in the Chinese Pharmacopoeia and Tibetan medicinal compounds in the Ministerial Standards by Ji Zang, Cai Rang-Zhou Tai, Jie-Jia Nan, Cai Rang-Nanjia

“…Different weights were applied to calculate the comprehensive similarity between the formulas. …”
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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. …”
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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. …”
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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. …”
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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. …”
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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. …”
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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. …”
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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. …”
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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). …”
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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. …”
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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

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Supercontinuum Generation at 1310nm in a Highly Nonlinear Photonic Crystal Fiber with a Minimum Anomalous Group Velocity Dispersion by Ashkan Ghanbari, Ali Sadr, Hadi Tat Hesari

“…ABSTRACT:In present study ,we intend to investigate the evolution of supercontinuum generation (SCG) through triangular photonic crystal fiber (PCF) at 1310nm by using both full-vector multipole method (M.P.M) and novel concrete algorithms: symmetric  split-step fourier (SSF) and  fourth order runge kutta (RK4) which is an accurate method to solve the general  nonlinear schrodinger equation (GNLSE). …”
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Quantitative Analysis of Sulfur Elements in Mars-like Rocks Based on Multimodal Data by Yuhang Dong, Zhengfeng Shi, Junsheng Yao, Li Zhang, Yongkang Chen, Junyan Jia

“…Furthermore, to optimize model performance, different feature selection algorithms were evaluated. …”
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Explainable Predictive Model for Suicidal Ideation During COVID-19: Social Media Discourse Study by Salah Bouktif, Akib Mohi Ud Din Khanday, Ali Ouni

“…ConclusionsConsidering the dynamic nature of suicidal behavior posts, we proposed a fused architecture that captures both localized and generalized contextual information that is important for understanding the language patterns and predict the evolution of suicidal ideation over time. According to Local Interpretable Model-Agnostic Explanations (LIME) and Shapley Additive Explanations (SHAP) XAI algorithms, there was a drift in the features during and before COVID-19. …”
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Development and validation of machine learning-based diagnostic models using blood transcriptomics for early childhood diabetes prediction by Xin Huang, Xin Huang, Di Ouyang, Weiming Xie, Huawei Zhuang, Siyu Gao, Pan Liu, Lizhong Guo

“…Performance was evaluated using accuracy, precision, recall, and F1-score metrics. …”
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