Analysis of immune characteristics and inflammatory mechanisms in COPD patients: a multi-layered study combining bulk and single-cell transcriptome analysis and machine learning by Changjin Wei, Yongfeng Zhu, Caiming Chen, Feipeng Li, Li Zheng

“…Inflammatory-related COPD feature genes were selected using Lasso regression and random forest algorithms, and a COPD risk prediction model was constructed. …”
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Research on formant estimation algorithm for high order optimal LPC root value screening by Hua LONG, Shumeng SU

“…In terms of the robustness of the algorithm and the overall performance comparison of different methods,the proposed algorithm can extract the formant robustly from order 9 to 22, and the model algorithm shows the optimal performance when the formant is extracted from order 18. …”
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Characterization of lactylation modification subtypes and the promoting role of CCL20 in hepatocellular carcinoma progression by Li-Hong Wu, Liu Yang, Xiang-Xu Wang, Shuang Bai, Xi Yan, Jing Wei, Jun Wang, Fei Tian

“…The CIBERSORT algorithm was utilized to analyze immune cell infiltration. …”
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Glypican-3 regulated epithelial mesenchymal transformation-related genes in osteosarcoma: based on comprehensive tumor microenvironment profiling by Jiaming Zhang, Wei Wang

“…The least absolute shrinkage and selection operator (LASSO) algorithm was applied to screen candidate genes for developing a prognostic model. …”
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Identification of potential pathogenic genes associated with the comorbidity of rheumatoid arthritis and renal fibrosis using bioinformatics and machine learning by Jiao Qiu, Yalin Xu, Luyuan Tong, Xingchun Yang, Xiao Wu

“…Subsequently, functional enrichment analysis was performed to clarify the biological functions of these genes. Machine learning algorithms were used to screen for the hub RA-RF differential expression genes, and then a Logistic Regression (LR) model was constructed. …”
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Genome-wide expression in human whole blood for diagnosis of latent tuberculosis infection: a multicohort research by Fan Jiang, Fan Jiang, Fan Jiang, Yanhua Liu, Linsheng Li, Linsheng Li, Ruizi Ni, Ruizi Ni, Yajing An, Yajing An, Yufeng Li, Yufeng Li, Lingxia Zhang, Wenping Gong

“…A Naive Bayes (NB) model incorporating these two markers demonstrated robust diagnostic performance: training set AUC: median = 0.8572 (inter-quartile range 0.8002, 0.8708), validation AUC = 0.5719 (0.51645, 0.7078), and subgroup AUC = 0.8635 (0.8212, 0.8946).ConclusionOur multicohort analysis established an NB-based diagnostic model utilizing S100A12/S100A8, which maintains diagnostic accuracy across diverse geographic, ethnic, and clinical variables (including HIV co-infection), highlighting its potential for clinical translation in LTBI/ATB differentiation.…”
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Defects Detection in Screen-Printed Circuits Based on an Enhanced YOLOv8n Algorithm by Xinyu Zhang, Jia Wang, Dan Jiang, Yang Li, Xuewei Wang, Han Zhang

“…To address these challenges, a self-made SPC defect data set and an enhanced CAAB-YOLOv8n detection algorithm were developed. A CAD module was integrated into the backbone network to improve the model’s ability to detect bar-shaped features. …”
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Mitochondrial autophagy-related gene signatures associated with myasthenia gravis diagnosis and immunity by Shan Jin, Junbin Yin, Wei Li, Ni Mao

“…Multiple machine learning algorithms were applied to screen and verify the diagnostic genes of intersection genes. …”
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Machine Learning-Assisted NIR Spectroscopy for Dynamic Monitoring of Leaf Potassium in Korla Fragrant Pear by Mingyang Yu, Weifan Fan, Junkai Zeng, Yang Li, Lanfei Wang, Hao Wang, Feng Han, Jianping Bao

“…By measuring leaf potassium content at the fruit setting, expansion, and maturity stages (decreasing from 1.60% at fruit setting to 1.14% at maturity), this study reveals its dynamic change pattern and establishes a high-precision prediction model by combining near-infrared spectroscopy (NIRS) with machine learning algorithms. …”
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Machine learning prediction model with shap interpretation for chronic bronchitis risk assessment based on heavy metal exposure: a nationally representative study by Tiansheng Xia, Kaiyu Han

“…Methods Weighted logistic regression was used to assess the association of 14 blood and urine heavy metals with CB based on nationally representative samples from the 2005–2015 National Health and Nutrition Examination Survey (NHANES). The Boruta algorithm was further applied to screen the characteristic variables and construct 10 ML models. …”
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AI-based Assessment of Risk Factors for Coronary Heart Disease in Patients With Diabetes Mellitus and Construction of a Prediction Model for a Treatment Regimen by Zhen Gao, Qiyuan Bai, Mingyu Wei, Hao Chen, Yan Yan, Jiahao Mao, Xiangzhi Kong, Yang Yu

“…Conclusions: Using machine-learning algorithms, we built a prediction model of a treatment plan for patients with concomitant DM and CHD by integrating patients' information and screened the best feature set containing 15 features, which provides help and strategies to develop the best treatment plan for patients with concomitant DM and CHD.…”
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Low-cost and scalable machine learning model for identifying children and adolescents with poor oral health using survey data: An empirical study in Portugal. by Susana Lavado, Eduardo Costa, Niclas F Sturm, Johannes S Tafferner, Octávio Rodrigues, Pedro Pita Barros, Leid Zejnilovic

“…Such a model could enable scalable and cost-effective screening and targeted interventions, optimizing limited resources to improve oral health outcomes. …”
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Application of Improved Electromagnetism-like Mechanism Algorithm on Massive Remote Sensing Image Screening by Yingjie Fang, Kun Liu, Xun Zhang, Gang Lin, Huibing Wang, Lina Dong, Su Li

“…To improve the screening efficiency, people usually adopt the greedy algorithm for data screening, which may lead to becoming trapped in a local optimal solution. …”
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A novel prediction model for the prognosis of non-small cell lung cancer with clinical routine laboratory indicators: a machine learning approach by Yuli Wang, Na Mei, Ziyi Zhou, Yuan Fang, Jiacheng Lin, Fanchen Zhao, Zhihong Fang, Yan Li

“…Finally, critical variables in the optimal model were screened based on the interpretable algorithms to build a decision tree to facilitate clinical application. …”
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The Automatable Activity–Based Approach to Complexity Unit Scoring as a task-specific model approach to monetizing outcomes of pathology artificial intelligence solutions by Stavros Pantelakos, Martha Nifora, Georgios Agrogiannis

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Development and validation of an early predictive model for hemiplegic shoulder pain: a comparative study of logistic regression, support vector machine, and random forest by Qiang Wu, Qiang Wu, Fang Zhang, Yuchang Fei, Zhenfen Sima, Shanshan Gong, Qifeng Tong, Qingchuan Jiao, Hao Wu, Jianqiu Gong, Jianqiu Gong

“…ObjectiveIn this study, we aim to identify the predictive variables for hemiplegic shoulder pain (HSP) through machine learning algorithms, select the optimal model and predict the occurrence of HSP.MethodsData of 332 stroke patients admitted to a tertiary hospital in Zhejiang Province from January 2022 to January 2023 were collected. …”
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LumaCam: a novel class of position-sensitive event mode particle detectors using scintillator screens by Alexander Wolfertz, Alex Gustschin, Michael Schulz, Alexander M. Long, Anton Khaplanov, Tsviki Y. Hirsh, Andrei Nomerotski, Manuel Morgano, Anton Tremsin, Giacomo Mauri, G. Jeff Sykora, Adrian Losko

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Molecular characterization and prognostic modeling associated with M2-like tumor-associated macrophages in breast cancer: revealing the immunosuppressive role of DLG3 by Ziqiang Wang, Jing Zhang, Huili Chen, Xinyu Zhang, Kai Zhang, Feiyue Zhang, Yiluo Xie, Hongyu Ma, Linfeng Pan, Qiang Zhang, Min Lu, Hongtao Wang, Chaoqun Lian

“…Consensus clustering analysis identified three molecular subtypes with distinct clinical features, and we explored potential differences in genomic mutations, pathway enrichment, and immune infiltration in patients between subtypes. Machine learning algorithms were used to screen key genes and construct M2-like macrophage-associated prognostic models. …”
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Targeted Detection of 76 Carnitine Indicators Combined with a Machine Learning Algorithm Based on HPLC-MS/MS in the Diagnosis of Rheumatoid Arthritis by Rui Zhang, Juan Wang, Xiaonan Zhai, Yuanbing Guo, Lei Zhou, Xiaoyan Hao, Liu Yang, Ruiqing Xing, Juanjuan Hu, Jiawei Gao, Fengjuan Wang, Jun Yang, Jiayun Liu

“…The diagnostic model derived from the screened markers was validated using three machine learning algorithms. …”
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Plasma proteomics-based risk scores for psoriasis prediction: a novel approach to early diagnosis by Siyu Wei, Zehong Yue, Chen Sun, Yuping Zou, Haiyan Chen, Junxian Tao, Jing Xu, Yuan Xu, Ning Wang, Yan Guo, Qinduo Ren, Chang Wang, Songlin Lu, Ye Ma, Yu Dong, Chen Zhang, Hongmei Sun, Guoping Tang, Fanwu Kong, Wenhua Lv, Zhenwei Shang, Mingming Zhang, Yongshuai Jiang, Hongchao Lyu

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