Postpartum Haemorrhage Risk Prediction Model Developed by Machine Learning Algorithms: A Single-Centre Retrospective Analysis of Clinical Data by Wenhuan Wang, Chanchan Liao, Hongping Zhang, Yanjun Hu

Get full text

Comparative Analysis of Machine Learning Algorithms for Potential Evapotranspiration Estimation Using Limited Data at a High-Altitude Mediterranean Forest by Stefanos Stefanidis, Konstantinos Ioannou, Nikolaos Proutsos, Ilias Karmiris, Panagiotis Stefanidis

Get full text

Enhanced soil organic carbon mapping in Gannan’s alpine meadows: A comparative analysis of machine learning models and satellite data by Xingyu Liu, Meiling Zhang, Ziming Ma

“…This study targets the Gannan region, a key livestock area in China, where accurate soil organic carbon density (SOCD) mapping using remote sensing and machine learning is crucial. We explored the effectiveness of different satellite sensors, including optical (Sentinel-2) and radar (Sentinel-1), in SOCD prediction models, assessing uncertainties. …”
Get full text

Bidders Recommender for Public Procurement Auctions Using Machine Learning: Data Analysis, Algorithm, and Case Study with Tenders from Spain by Manuel J. García Rodríguez, Vicente Rodríguez Montequín, Francisco Ortega Fernández, Joaquín M. Villanueva Balsera

Get full text

Comparative Performance of Autoencoders and Traditional Machine Learning Algorithms in Clinical Data Analysis for Predicting Post-Staged GKRS Tumor Dynamics by Simona Ruxandra Volovăț, Tudor Ovidiu Popa, Dragoș Rusu, Lăcrămioara Ochiuz, Decebal Vasincu, Maricel Agop, Călin Gheorghe Buzea, Cristian Constantin Volovăț

“…<b>Methods:</b> This retrospective analysis utilized clinical data from 77 patients treated at the “Prof. …”
Get full text

Prescriptive Predictors of Mindfulness Ecological Momentary Intervention for Social Anxiety Disorder: Machine Learning Analysis of Randomized Controlled Trial Data by Nur Hani Zainal, Hui Han Tan, Ryan Yee Shiun Hong, Michelle Gayle Newman

Get full text

Integrating Molecular Perspectives: Strategies for Comprehensive Multi-Omics Integrative Data Analysis and Machine Learning Applications in Transcriptomics, Proteomics, and Metabolomics by Pedro H. Godoy Sanches, Nicolly Clemente de Melo, Andreia M. Porcari, Lucas Miguel de Carvalho

“…We discuss combined omics integration approaches, correlation-based strategies, and machine learning techniques that utilize one or more types of omics data. …”
Get full text

Advancing Built-Up Area Monitoring Through Multi-Temporal Satellite Data Fusion and Machine Learning-Based Geospatial Analysis by Alessandro Vitale, Francesco Lamonaca

Get full text

Data-Driven Analysis of Fluorescence Lifetime Imaging Experiments: Unraveling the Signal/Stress Relationship of Polluted Microalgae Cells with Machine Learning by Erwan Privat, Ilaria Fortunati, Camilla Ferrante, Sergio Rampino, Antonino Polimeno

Get full text

Spatial Distribution Pattern of Forests in Yunnan Province in 2022: Analysis Based on Multi-Source Remote Sensing Data and Machine Learning by Guangyang Li, Hongyan Lai, Bangqian Chen, Xiong Yin, Weili Kou, Zhixiang Wu, Zongzhu Chen, Guizhen Wang

Get full text

Bioinformatic Analysis of Complex In Vitro Fertilization Data and Predictive Model Design Based on Machine Learning: The Age Paradox in Reproductive Health by Myrto A. Lantzi, Eleni Papakonstantinou, Dimitrios Vlachakis

“…Concurrently, the utilization of machine learning algorithms has facilitated the development and implementation of predictive models. …”
Get full text

THE ROLE OF DATA VISUALIZATION IN ENHANCING TEXTUAL ANALYSIS by P. Milev

“…The impact of machine learning and artificial intelligence on data visualization, the representation of uncertainty, and the democratization of data visualization tools are thoroughly analyzed. …”
Get full text

Applications of Machine Learning Algorithms in Geriatrics by Adrian Stancu, Cosmina-Mihaela Rosca, Emilian Marian Iovanovici

“…The analysis highlights gaps regarding the explainability of the models used, the transparency of cross-sectional datasets, and the validity of the data in real clinical contexts. …”
Get full text

Identification of biomarkers for knee osteoarthritis through clinical data and machine learning models by Wei Chen, Haotian Zheng, Binglin Ye, Tiefeng Guo, Yude Xu, Zhibin Fu, Xing Ji, Xiping Chai, Shenghua Li, Qiang Deng

“…This study aimed to develop and validate biomarker-based predictive models for KOA diagnosis using machine learning techniques. Clinical data from 2594 samples were obtained and stratified into training and validation datasets in a 7:3 ratio. …”
Get full text

Forecasting Air Pollution Contingencies Using Predictive Analytic Techniques by Raul Ramirez-Velarde, Oscar Esquivel-Flores, Gerardo Mejía-Velázquez

“…For categorical variables, each linear combination probability is estimated using a window-based estimation technique or a machine learning algorithm to determine the class of a particular sample. …”
Get full text

Rapid detection of honey adulteration using machine learning on gas sensor data by Mehmet MİLLİ, Nursel SÖYLEMEZ MİLLİ, İsmail Hakkı PARLAK

Get full text

A Comparison of Approaches for Handling Concept Drifts in Data Processed With Machine Learning by Emanuel Valerio Pereira, Wendley Souza da Silva

Get full text

Applying machine learning to classify table olives using bacterial metataxonomic data by Elio López-García, Antonio Benítez-Cabello, Francisco Noé Arroyo-López

“…Moreover, advances in bioinformatics and machine learning (ML) have expanded resources for analyzing these metataxonomic data. …”
Get full text

Machine Learning and Data Science in Social Sciences: Methods, Applications, and Future Directions by Elias Dritsas, Maria Trigka

“…Artificial intelligence (AI) is transforming social science research by enabling scalable data analysis, predictive modeling, and causal inference, thereby reshaping the methodological foundations of fields such as political science, economics, and psychology. …”
Get full text

Innovative data techniques for centrifugal pump optimization with machine learning and AI model. by Gaurav Sandeep Dave, Amar Pradeep Pandhare, Atul Prabhakar Kulkarni, Dhananjay Vasant Khankal

“…The data recorded from DAQ system undergoes thorough in-depth analysis, processing & transformation before being incorporated into machine learning (ML) or artificial intelligence models. …”
Get full text