From Machine Learning-Based to LLM-Enhanced: An Application-Focused Analysis of How Social IoT Benefits from LLMs by Lijie Yang, Runbo Su

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A privacy-enhanced framework for collaborative Big Data analysis in healthcare using adaptive federated learning aggregation by Rahul Haripriya, Nilay Khare, Manish Pandey, Sreemoyee Biswas

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Machine Learning Classifiers Based Classification For IRIS Recognition by Bahzad Taha Chicho, Adnan Mohsin Abdulazeez, Diyar Qader Zeebaree, Dilovan Assad Zebari

“…Classification is the most widely applied machine learning problem today, with implementations in face recognition, flower classification, clustering, and other fields. …”
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A Comparative Analysis of Machine Learning and Deep Learning Techniques for Accurate Market Price Forecasting by Olamilekan Shobayo, Sidikat Adeyemi-Longe, Olusogo Popoola, Obinna Okoyeigbo

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Toward learning steelmaking—A review on machine learning for basic oxygen furnace process by Maryam Khaksar Ghalati, Jianbo Zhang, G. M. A. M. El‐Fallah, Bogdan Nenchev, Hongbiao Dong

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Application of the program for artificial intelligence analytics of paper text and segmentation by specified parameters in clinical practice by A. A. Komkov, V. P. Mazaev, S. V. Ryazanova, A. A. Kobak, E. V. Bazaeva, D. N. Samochatov, E. V. Koshkina, Е. V. Bushueva, O. M. Drapkina

“…To evaluate the effectiveness of the RuPatient electronic heart record (EHR) system in real clinical practice for extracting and structuring medical data.Material and methods. Extraction and recognition of data using EHR from various following sources: outpatient records, statements, routine medical reports, epicrisis and other structured and unstructured medical information based on the developed technology of intelligent text analytics, optical character recognition, for specified words and phrases, and the use of machine learning elements. …”
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Data Preprocessing Techniques for AI and Machine Learning Readiness: Scoping Review of Wearable Sensor Data in Cancer Care by Bengie L Ortiz, Vibhuti Gupta, Rajnish Kumar, Aditya Jalin, Xiao Cao, Charles Ziegenbein, Ashutosh Singhal, Muneesh Tewari, Sung Won Choi

“…ObjectiveThis study aims to conduct a scoping review of preprocessing techniques used on raw wearable sensor data in cancer care, specifically focusing on methods implemented to ensure their readiness for artificial intelligence and machine learning (AI/ML) applications. …”
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The data recovery strategy on machine learning against false data injection attacks in power cyber physical systems by Qinxue Li, Xiaofen Yang, Xuhuan Xie, Guiyun Liu

“…To mitigate that threat, this paper is concerned with a new data recovery strategy on machine learning against false data injection attacks (FDIAs) in PCPSs. …”
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Designing Predictive Analytics Frameworks for Supply Chain Quality Management: A Machine Learning Approach to Defect Rate Optimization by Zainab Nadhim Jawad, Balázs Villányi

“…This study presents a machine learning (ML)-driven predictive analytics framework designed to forecast defect rates and optimize quality control processes. …”
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Enabling Advanced Land Cover Analytics: An Integrated Data Extraction Pipeline for Predictive Modeling With the Dynamic World Dataset by Victor Radermecker, Andrea Zanon, Nancy Thomas, Annita Vapsi, Saba Rahimi, Rama Ramakrishnan, Daniel Borrajo

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Medical Diagnostic Systems Using Artificial Intelligence (AI) Algorithms: Principles and Perspectives by Simarjeet Kaur, Jimmy Singla, Lewis Nkenyereye, Sudan Jha, Deepak Prashar, Gyanendra Prasad Joshi, Shaker El-Sappagh, Md. Saiful Islam, S. M. Riazul Islam

Subjects: “…Big data analytics…”
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Analysis of Vertical Ground Reaction Force Data in Predicting Parkinson’s Disease by Varun Jain

“…A Fourier Analysis and several support vector machine learning models were computed in MATLAB to classify whether an individual had Parkinson’s disease. …”
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Can the Plantar Pressure and Temperature Data Trend Show the Presence of Diabetes? A Comparative Study of a Variety of Machine Learning Techniques by Eduardo A. Gerlein, Francisco Calderón, Martha Zequera-Díaz, Roozbeh Naemi

“…This study aimed to explore the potential of predicting diabetes by analyzing trends in plantar thermal and plantar pressure data, either individually or in combination, using various machine learning techniques. …”
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MACHINE LEARNING AS A CORPORATION'S TOOL FOR SELECTION OF SUPPLIERS by V. V. Baklushinskii, E. V. Pustynnikova

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Machine Learning Model for Predicting Net Environmental Effects by Sellappan Palaniappan, Rajasvaran Logeswaran, Shapla Khanam, Zhang Yujiao

“…This study presents a proof-of-concept machine learning model for predicting net environmental effects using synthetic data. …”
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A review of machine learning applications in heart health by Ava Perrone, Taghi M. Khoshgoftaar

“…This review contributes an analysis of current machine learning methods in stroke and heart attack research, highlighting key gaps such as limited use of multimodal data, external validation, and class imbalance mitigation. …”
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A density clustering-based network performance failure big data analysis algorithm by Xiang LI, Yuan LI, Zifei ZHANG, Zhe YANG

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A predictive healthcare model using machine learning and psychological factors for medication adherence by Junwu Dong, Minyi Chu, Yirou Xu

“…This study aims to develop a predictive model for medication adherence behaviour (MAB) employing machine learning techniques, addressing the limitations of traditional correlation-based approaches. …”
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Integration of Machine Learning and Wavelet Algorithms for Processing Probing Signals: An Example of Oil Wells by Zukhra Abdiakhmetova, Zhanerke Temirbekova

“…By integrating wavelet-based feature extraction with machine learning-driven analysis, this approach enhances the ability to detect complex wave propagation patterns, leading to more precise subsurface modeling. …”
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Machine Learning Modeling of Foam Concrete Performance: Predicting Mechanical Strength and Thermal Conductivity from Material Compositions by Leifa Li, Wangwen Sun, Askar Ayti, Wangping Chen, Zhuangzhuang Liu, Lauren Y. Gómez-Zamorano

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