Investigating immune cell infiltration and gene expression features in pterygium pathogenesis by Ji Yang, Ya-Nan Chen, Chen-Yan Fang, Yan Li, Hong-Qin Ke, Rui-Qin Guo, Ping Xiang, Yun-Ling Xiao, Li-Wei Zhang, Hai Liu

“…There were 52 co-DEGs shared by both datasets, and four candidate biomarkers (FN1, SPRR1B, SERPINB13, EGR2) with potential diagnostic value were identified through machine learning algorithms. …”
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Hemoglobin state-flux: A finite-state model representation of the hemoglobin signal for evaluation of the resting state and the influence of disease. by Randall L Barbour, Harry L Graber, San-Lian S Barbour

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Long-term prognosis of 47 pediatric patients with Blau syndrome in China by Xinwei Shi, Jianghong Deng, Junmei Zhang, Xiaozhen Zhao, Yinan Zhao, Li Li, Fengqiao Gao, Weiying Kuang, Jiang Wang, Xiaohua Tan, Chao Li, Shipeng Li, Caifeng Li

“…A Bayesian network was constructed to integrate prediction algorithms of genetic mutations and clinical manifestations, exploring the complex relationship between genotype and phenotype through R (Version 4.4.1, R Core Development Team). …”
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Examining the Role of Social Media in New Social Movements A Case Study of the Black Lives Matter Movement by Ali Davari, Mostafa Ghaffari

“…Additionally, the movement’s reliance on private platforms such as Twitter and Facebook raises concerns about censorship, algorithmic bias, and data privacy—issues not addressed in Melucci’s original framework.Conclusion: By integrating Melucci’s theoretical insights with the lived realities of the Black Lives Matter movement, this study demonstrates how social media can both strengthen and complicate the dynamics of new social movements. …”
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A panting behavior-driven assessment framework for summer ventilation quality optimization in layer houses by Zixuan Zhou, Lihua Li, Hao Xue, Yuchen Jia, Yao Yu, Zongkui Xie, Yuhan Gu

“…K-means clustering and linear regression algorithms were employed to establish a quantitative correlation curve between ventilation quality and panting behavior, forming a Normal-Alert-Danger ventilation quality (VQ) classification standard. …”
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Project quality, regulation quality by Elena Mussinelli

“…Instead, deductive design approaches seem to prevail today, due to the growing availability of algorithmic procedures that do not merely support the design process, but develop it in an almost automated manner through conditioning and prevailing indicators and parameters. …”
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Machine learning-based prediction model for lung ischemia-reperfusion injury: insights from disulfidptosis-related genes by Yanpeng Zhang, Yanpeng Zhang, Yanpeng Zhang, Jingyang Sun, Jingyang Sun, Jingyang Sun, Yihan Lin, Yihan Lin, Yihan Lin, Rongxuan Jiang, Rongxuan Jiang, Rongxuan Jiang, Niuniu Dong, Niuniu Dong, Niuniu Dong, Huanhuan Dong, Huanhuan Dong, Huanhuan Dong, Peng Li, Peng Li, Peng Li, Jinteng Feng, Jinteng Feng, Jinteng Feng, Zijiang Zhu, Guangjian Zhang, Guangjian Zhang, Guangjian Zhang

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Habitat radiomics analysis for progression free survival and immune-related adverse reaction prediction in non-small cell lung cancer treated by immunotherapy by Yuemin Wu, Wei Zhang, Xiao Liang, Pengpeng Zhang, Mengzhe Zhang, Yuqin Jiang, Yanan Cui, Yi Chen, Wenxin Zhou, Qi Liang, Jiali Dai, Chen Zhang, Jiali Xu, Jun Li, Tongfu Yu, Zhihong Zhang, Renhua Guo

“…Results Our study introduces a radiomic nomogram model that integrates clinical and habitat radiomic features to identify patients who may benefit from ICIs or experience irAEs. …”
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Urban Tree Canopy Mapping and Analysis Using Iterative Annotation Method and Deep Learning: A Case Study in Beijing by Yulong Ding, Ximin Cui, Zhengchao Chen, Zeqing Wang, Debao Yuan, Xiang Meng, Xuan Yang, Yue Xu, Xiangyu Tian

“…To address this, we propose an iterative method based on intersection over union (IoU), integrating multiscale segmentation and nearest-neighbor classification algorithms. …”
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Contrast-enhanced ultrasound radiomics model for predicting axillary lymph node metastasis and prognosis in breast cancer: a multicenter study by Shi Yu Li, Yue Ming Li, Yong Qi Fang, Zhi Ying Jin, Jun Kang Li, Xiao Meng Zou, Si Si Huang, Rui Lan Niu, Nai Qing Fu, Yu Hong Shao, Xuan Tong Gong, Mao Ran Li, Wei Wang, Zhi Li Wang

“…LASSO regression was employed to select radiomic features (RFs), while eight machine learning algorithms were utilized to construct radiomic models based on US, CDFI, and CEUS. …”
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Thermal comfort and energy related occupancy behavior in Dutch residential dwellings by Anastasios Ioannou

“…Such pattern recognition algorithms can be more effective in the era of mobile internet, which allows the capturing of huge amounts of data. …”
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The future of critical care: AI-powered mortality prediction for acute variceal gastrointestinal bleeding and acute non-variceal gastrointestinal bleeding patients by Zhou Liu, Guijun Jiang, Liang Zhang, Palpasa Shrestha, Yugang Hu, Yi Zhu, Guang Li, Yuanguo Xiong, Liying Zhan

“…The SHAP visualization shows the weights of two ML models feature variables and the average sharp values of variables. Meanwhile, SHAP waterfall outputs the model prediction process with true positive and negative patients. …”
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Leveraging machine learning for data-driven building energy rate prediction by Nasim Eslamirad, Mehdi Golamnia, Payam Sajadi, Francesco Pilla

“…The results demonstrate that the RF model outperformed other algorithms, achieving the highest classification accuracy, with AUC values ranging from 0.77 to 0.83. …”
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Extended version of decision making model for industrial robot selection via fractional continuous fuzzy information by Asaf Khan, Saifullah Khan, Ariana Abdul Rahimzai, Saleem Abdullah

“…Abstract Fractional fuzzy sets are widely used in decision-making problems; however, they often face limitations in accurately modeling membership and non-membership values. These sets are considered classical models because they use only specific values from the closed interval [0, 1], which leads to a rigid decision-making structure. …”
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COMPARATIVE ANALYSIS OF DOUBLE DEEP Q-NETWORK AND PROXIMAL POLICY OPTIMIZATION FOR LANE-KEEPING IN AUTONOMOUS DRIVING by Ariful Islam Sabbir

“…This article gives a comparative examination of two reinforcement learning (RL) algorithms—Double Deep Q-Network and Proximal Policy Optimization—for lanekeeping across discrete and continuous action spaces. …”
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Machine Learning Applied to Improve Prevention of, Response to, and Understanding of Violence Against Women by Mariana Carolyn Cruz-Mendoza, Roberto Angel Melendez-Armenta, Juana Canul-Reich, Julio Muñoz-Benítez

“…This study introduces Mujer Segura, an innovative web application designed to collect structured data on IPV cases and predict their severity using machine learning models. The methodology integrates Random Forest (RF) and Gradient Boosting Classifier (GBC) algorithms to classify IPV cases by leveraging historical data for predictive analysis. …”
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An Ensemble Learning Approach for Drought Analysis and Forecasting in Central Bangladesh by Md. Alomgir Hossain, Momotaz Begum, Md. Nasim Akhtar, Md. Alamin Talukder, Nomanur Rahman, Mahfuzur Rahman

“…The study revealed that integrating ARIMA with ML algorithms improved forecasting accuracy, achieving over 92.0% accuracy in predicting SPI and SPEI, thereby significantly enhancing drought prediction capabilities.…”
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Economic evaluation of diagnostic tests for Thai patients with tuberculosis: A dynamic transmission model approach. by Natthakan Chitpim, Naiyana Praditsitthikorn, Lisa J White, Aronrag Meeyai, Jiraphun Jittikoon, Kornkanok Bunwong, Sitaporn Youngkong, Montarat Thavorncharoensap, Surakameth Mahasirimongkol, Wanvisa Udomsinprasert, Usa Chaikledkaew

“…Compared to SSM with culture and DST, the ICER values (Baht per QALY gained) of TB-LAMP Add-On (3,563), Xpert MTB/RIF Add-On (3,670), and TB-LAMP Initial (6,429) indicated that these algorithms were cost-effective, while Xpert MTB/RIF Initial emerged as a cost-saving option. …”
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Interpretable web-based machine learning model for predicting intravenous immunoglobulin resistance in Kawasaki disease by Ying He, Fan Lin, Xin Zheng, Qiaobin Chen, Meng Xiao, Xiaoting Lin, Hongbiao Huang

“…Existing predictive models do not integrate multiple machine learning (ML) algorithms or facilitate real-time clinical use. …”
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Prediction of Reservoir Flow Capacity in Sandstone Formations: A Comparative Analysis of Machine Learning Models by Micheal Ayodeji Ogundero, Taiwo Adelakin, Kehinde Orolu, Isaac Femi Johnson, Theophilus Akinfenwa Fashanu, Kingsley Abhulimen

“… Sand production is one of the major challenges in the oil and gas industry, impacting the operational integrity and economic efficiency of oil extraction activities. …”
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