Leveraging the integration of bioinformatics and machine learning to uncover common biomarkers and molecular pathways underlying diabetes and nephrolithiasis by Xudong Shen, Xudong Shen, Xudong Shen, Guoxiang Li, Guoxiang Li, Guoxiang Li, Junfeng Yao, Junfeng Yao, Junfeng Yao, Junping Yang, Xiaobo Ding, Xiaobo Ding, Xiaobo Ding, Zongyao Hao, Zongyao Hao, Zongyao Hao, Yan Chen, Yang Chen, Yang Chen, Yang Chen

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Machine learning-driven multi-omics analysis identifies a prognostic gene signature associated with programmed cell death and metabolism in hepatocellular carcinoma by Xiang Li, Donghao Yin, Jiahao Geng, Yanyu Xu, Zijing Xu, Xuemeng Yang, Quanwei Li, Zimeng Shang, Zhiyun Yang, Zhong Xu, Jiabo Wang, Enxiang Zhang, Xinhua Song

“…The intersecting DEGs from both datasets were analyzed using univariate Cox regression, and a prognostic risk score model was constructed through machine learning algorithms. The model was subsequently evaluated in the context of the immune microenvironment and its relevance to immunotherapeutic responses. …”
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Assessing the construction site supervisory attributes in effectuating mathematical theories and applications to construction operations by Kesavan Manoharan, Pujitha Dissanayake, Chintha Pathirana, Dharsana Deegahawature, Renuka Silva

“…Design/methodology/approach – A total of 62 construction site supervisors were trained as part of a new apprenticeship programme. …”
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Pengembangan Media Pembelajaran Interaktif pada Mata Kuliah Teori dan Praktik Plambing di Program Studi S1 PVKB UNJ

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Combining realist evaluation and appreciative inquiry: A participatory, learning-focused methodology for tourism interventions by Jenny Suno Wu, Pete Barbrook-Johnson, Xavier Font, Anna Torres-Delgado

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Predictive biomarkers and molecular subtypes in DLBCL: insights from PCD gene expression and machine learning by Tiantian He, Jie Geng, Chuandong Hou, Hongyi Li, Hong Zhang, Peng Zhao, Peifeng He, Xuechun Lu

“…Additionally, 12 machine learning algorithms were employed to construct predictive models for DLBCL, with performance evaluated using AUC and F-score metrics. …”
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An Application Programming Interface (API) Sensitive Data Identification Method Based on the Federated Large Language Model by Jianping Wu, Lifeng Chen, Siyuan Fang, Chunming Wu

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Research discussion groups as a component of the development of practical skills of students in the field of training “Construction” by N. I. Taraseeva, O. V. Baulina, N. A. Dezhinova

“…The modern educational process, including theoretical and practical development of the basic educational program, provides that 40% of the basic information the student is receiving during the classes, the remaining 60% — for self-study. …”
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Effect of a Web-Based Educational Program on Prevention of Tobacco Smoking among Male Adolescents: An Application of Prototype Willingness Model by Alireza Heidarnia, Majid Barati, Shamsoddin Niknami, Hamid Allahverdipour, Saeed Bashirian

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Interpretable machine learning approaches to assess the compressive strength of metakaolin blended sustainable cement mortar by Naseer Muhammad Khan, Liqiang Ma, Waleed Bin Inqiad, Muhammad Saud Khan, Imtiaz Iqbal, Muhammad Zaka Emad, Saad S. Alarifi

“…Thus, this study was conducted to develop reliable empirical prediction models to assess CS of MK-based mortar from its mixture proportion using machine learning algorithms like gene expression programming (GEP), extreme gradient boosting (XGB), multi expression programming (MEP), bagging regressor (BR), and AdaBoost etc. …”
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RSS Tracking Control for AVs Under Bayesian-Network-Based Intelligent Learning Scheme by Kun Zhang, Kezhen Han, Nanbin Zhao

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Genetic programming-based algorithms application in modeling the compressive strength of steel fiber-reinforced concrete exposed to elevated temperatures by Mohsin Ali, Li Chen, Qadir Bux Alias Imran Latif Qureshi, Deema Mohammed Alsekait, Adil Khan, Kiran Arif, Muhammad Luqman, Diaa Salama Abd Elminaam, Amir Hamza, Majid Khan

“…However, extreme temperatures degrade concrete's material characteristics including stiffness and strength. The construction industry increasingly embraces machine learning (ML) to estimate concrete properties and optimize cost and time accurately. …”
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Programmed cell death signatures-driven microglial transformation in Alzheimer’s disease: single-cell transcriptomics and functional validation by Mi-Mi Li, Ying-Xia Yang, Ya-Li Huang, Shu-Juan Wu, Wan-Li Huang, Li-Chao Ye, Ying-Ying Xu

“…An integrated machine learning framework, combining 12 algorithms was used to construct a PCDS model. …”
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A rapid, low-cost deep learning system to classify strawberry disease based on cloud service by Guo-feng YANG, Yong YANG, Zi-kang HE, Xin-yu ZHANG, Yong HE

“…Although recent mobile vision technology based deep learning has achieved some success in overcoming the above problems, a key problem is how to construct a non-destructive, fast and convenient method to improve the efficiency of strawberry disease identification for the multi-region, multi-space and multi-time classification requirements. …”
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Community, Public Archaeology, and Co-construction of Knowledge Through the Educational Project of a Rural Mountain School by Fernández Mier Margarita, López Gómez Pablo, Sánchez-Broch Paloma, Carballido González Elías

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Development of Artificial Intelligence-Based Programs for the Diagnosis of Myocarditis in COVID-19 Using Chest Computed Tomography Data» by Ievgen A. Nastenko, Maksym O. Honcharuk, Vitalii O. Babenko, Mykola I. Lynnyk, Viktoria I. Ignatieva, Vitalii A. Yachnyk

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Predicting pile bearing capacity using gene expression programming with SHapley Additive exPlanation interpretation by Adil Khan, Majid Khan, Waseem Akhtar Khan, Muhammad Ali Afridi, Khawaja Atif Naseem, Ayesha Noreen

“…Abstract The accurate determination of pile-bearing capacity is crucial in construction projects to ensure the stability and safety of structures built on foundation piles. …”
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Predicting HIV self-testing intentions among Chinese college students: a dual-model analysis integrating health belief constructs and machine learning prioritization by Yan Jiang, Jing Li, Jing Li, Jingfen Lu, Liping He, Lin Hu, Jiazhen He, Xianli Huang, Yuchao Li

“…Random forest modeling prioritized these psychological constructs (mean decrease Gini >2.5), identifying male students and arts majors as critical subpopulations requiring targeted intervention.DiscussionOur dual-method analysis establishes that campus HIV control necessitates: 1) Gender-specific prevention programs addressing male students’ elevated risk exposure; 2) HBM-informed education strengthening self-efficacy and environmental cues; 3) Structural interventions reducing testing barriers through discreet service delivery. …”
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Defect Detection and Correction in OpenMP: A Static Analysis and Machine Learning-Based Solution by Norah A. Al-Johany, Fathy E. Eassa, Sanaa A. Sharaf, Eynas H. Balkhair, Sara M. Assiri

“…This paper presents a novel static analysis tool designed to detect and automatically correct concurrency-related defects in OpenMP programs. The tool performs lexical and syntactic analysis to extract OpenMP constructs, verify directive usage, and identify incorrect synchronization patterns. …”
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Spatiotemporal dynamics and key drivers of carbon emissions in regional construction sectors: Insights from a Random Forest Model by Zhonghan Yu, Qudsia Kanwal, Menghan Wang, Anissa Nurdiawati, Sami G. Al-Ghamdi

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