Exploring machine learning algorithms to predict short birth intervals and identify its determinants among reproductive-age women in East Africa by Tirualem Zeleke Yehuala, Bezawit Melak Fente, Sisay Maru Wubante

“…Method This study employs machine learning algorithms to predict short birth intervals among reproductive-age women in East Africa, using a dataset from Demographic and Health Surveys. …”
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A quantum machine learning framework for predicting drug sensitivity in multiple myeloma using proteomic data by M. Priyadharshini, B. Deevena Raju, A. Faritha Banu, P. Jagdish Kumar, V. Murugesh, Oleg Rybin

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Optimizing Smart City Strategies: A Data-Driven Analysis Using Random Forest and Regression Analysis by Omer Bafail

“…This study investigates the critical factors influencing smart city program success through a comprehensive data-driven analysis of 140 urban centers. Advanced machine learning techniques, specifically random forest algorithms, in conjunction with regression analysis, were employed to examine the correlations between 45 distinct attributes and respective smart city rankings. …”
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Modeling pine forest growing stock volume in subtropical regions of China using airborne Lidar data by Zige Lan, Xiandie Jiang, Guiying Li, Yagang Lu, Hongwen Yao, Dengsheng Lu

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Bean leaf image dataset annotated with leaf dimensions, segmentation masks, and camera calibrationMendeley Data by Karla Gabriele Florentino da Silva, Paulo Victor de Magalhães Rozatto, Kaio de Oliveira e Sousa, Lucas Dias Hudson, Artur Welerson Sott Meyer, Alemilson Fabiano Silva, Igor Tibiriçá Mendes, Alex Rodrigues Borges, Leandro Elias Morais, Luiz Maurílio da Silva Maciel, Saulo Moraes Villela, Helio Pedrini, Marcelo Bernardes Vieira

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Predicting depression in healthy young adults: A machine learning approach using longitudinal neuroimaging data by Ailing Zhang, Haobo Zhang

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Interdisciplinary medical education practices: building a case-driven interdisciplinary simulation system based on public datasets by Kangli Qiu, Tianshu Zeng, Wenfang Xia, Miaomiao Peng, Wen Kong

“…Results Five cases of gout, gastritis, cirrhosis, inflammatory bowel disease, and chronic obstructive pulmonary disease were utilized to master the standard process of data analysis across various datasets from multiple dimensions of the model algorithm, data analysis, and result display. …”
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Data-Driven Revolution in Academic Support for Mathematics Underachievers through Random Forest Individual and Hybrid Model by Asadi Srinivasulu, Vanithamani Palanisamy

“…Educational Data Mining, leveraging machine learning and data mining techniques, aims to predict student performance using available datasets. …”
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Model Design for Personnel Selection with Data Mining Approach (Case Study: A Commerce Bank of Iran) by Adel Azar, Parviz Ahmadi, Mohammad Vahid Sebt

“…This paper is investigating educated and objective methods of data analysis. It follows statistical rules, data mining techniques, and the relationship between entrance evaluation scores and personal and professional variables. …”
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Gamified Engagement for Data Crowdsourcing and AI Literacy: An Investigation in Affective Communication Through Speech Emotion Recognition by Eleni Siamtanidou, Lazaros Vrysis, Nikolaos Vryzas, Charalampos A. Dimoulas

“…The integration of these elements supports reliable and extensive data collection and the advancement of AI algorithms while concurrently developing various skills, such as emotional speech articulation and digital literacy. …”
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Regulation of the functional state of locomotive crew drivers using biofeedback training: factor analysis of experimental data by N. V. Shcherbina

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Quantifying Body Motion Synchrony in Autism Spectrum Disorder Using a Phase Difference Detection Algorithm: Toward a Novel Behavioral Biomarker by Jinhwan Kwon, Hiromi Kotani

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Online Prediction of Concrete Temperature During the Construction of an Arch Dam Based on a Sparrow Search Algorithm–Incremental Support Vector Regression Model by Yihong Zhou, Yu Deng, Fang Wang, Chunju Zhao, Huawei Zhou, Zhipeng Liang, Lei Lei

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Prediction of zero-dose children using supervised machine learning algorithm in Tanzania: evidence from the recent 2022 Tanzania Demographic and Health Survey by Beminate Lemma Seifu, Angwach Abrham Asnake, Alemayehu Kasu Gebrehana

“…Objectives This study aimed to employ machine learning algorithms to predict the factors contributing to zero-dose children in Tanzania, using the most recent nationally representative data.Design Cross-sectional study.Setting This study was conducted in Tanzania and used the most recent 2022 Tanzania Demographic and Health Survey, accessed from http://www.dhsprogram.com.Participants A total of 2120 children aged 12–23 months were included in this study.Outcome measure Seven classification algorithms were used in this study: logistic regression, decision tree classifier, random forest classifier (RF), support vector machine, K-nearest neighbour, XGBoost (XGB) and Naive Bayes. …”
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Noise Elimination for Wide Field Electromagnetic Data via Improved Dung Beetle Optimized Gated Recurrent Unit by Zhongyuan Liu, Xian Zhang, Diquan Li, Shupeng Liu, Ke Cao

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Classification of Precipitation Types and Investigation of Their Physical Characteristics Using Three-Dimensional S-Band Dual-Polarization Radar Data by Choeng-Lyong Lee, Wonbae Bang, Chia-Lun Tsai, GyuWon Lee

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An Iterative Method for Empirically-Based Q-Matrix Validation by Ragip Terzi, Jimmy de la Torre

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Decoding On-Field Roles in Football: A Sociological Analysis Using Intelligent MCDM Algorithm With Fuzzy Information for Player Positioning and Technical-Tactical Behavior by Lu Yan, Nannan Wang, Rui Chen

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THE CLINICAL CONFERENCE AS GUIDANCE TO FORMING INTERNS’ PROFESSIONAL COMPETENCIES DURING FORMATION IN THE UMSA’S DEPARTMENT OF POSTGRADUATED EDUCATION OF DENTISTS by T.P. Skripnikova, M.V. Khrebor, Ju. I. Sylenko, O.A. Pisarenko

“… Over 25 years the staff of the department of postgraduate education of dentists of the "UMSA" has been preparing the interns. …”
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Radiative heat and mass transfer significance through a permeable vertical plate with rotational effects: An artificial approach using the Levenberg–Marquardt algorithm by R. Kavitha, Kavikumar Jacob, Ahmad Haji Zadeh, Nagarajan Deivanayagampillai

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