Environmental factors affecting the BMI of older adults in the Philippines spatially assessed using machine learning by D.K. Mendoza, A.B. Araza, L.D. Groot, M. Mensink, R.C. Tan

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Survival analysis using machine learning in transplantation: a practical introduction by Andrea Garcia-Lopez, Maritza Jiménez-Gómez, Andrea Gomez-Montero, Juan Camilo Gonzalez-Sierra, Santiago Cabas, Fernando Giron-Luque

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Lightweighting the prediction process of urban states with parameter sharing and dilated operations by Peixiao Wang, Haolong Yang, Hengcai Zhang, Shifen Cheng, Feng Lu, Zeqiang Chen

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Inspiring from Galaxies to Green AI in Earth: Benchmarking Energy-Efficient Models for Galaxy Morphology Classification by Vasileios Alevizos, Emmanouil V. Gkouvrikos, Ilias Georgousis, Sotiria Karipidou, George A. Papakostas

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Importance of Spectral Information, Seasonality, and Topography on Land Cover Classification of Tropical Land Cover Mapping by Chansopheaktra Sovann, Stefan Olin, Ali Mansourian, Sakada Sakhoeun, Sovann Prey, Sothea Kok, Torbern Tagesson

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Classifying and diagnosing Alzheimer’s disease with deep learning using 6735 brain MRI images by Seyed Mohammad Mousavi, Khadijeh Moulaei, Leila Ahmadian

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Predicting age at first calving of dairy breed calves using whale optimization-based ensemble learning framework by Tewodros Shekure, Hussien Seid Worku, Sudhir Kumar Mohapatra, Tapan Kumar Das

“…Primary data collected by Ardayta Dairy Research Centre; Ethiopia is used for this research. …”
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A-XGBoost: a resilient machine learning technique for predicting crimes against women across cultures on low cardinality crime data by Mathew Nicho, Ahmed Hamed, Tarek Gaber, Jamal Hamad Al Arimi

“…Violence against women is a global problem requiring innovative preventive measures. This research leverages Accelerated XGBoost (A-XGBoost), to predict crime against women in two culturally distinct countries: Finland and the United Arab Emirates (UAE). …”
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Analyzing the performance of biomedical time-series segmentation with electrophysiology data by Richard Redina, Jakub Hejc, Marina Filipenska, Zdenek Starek

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Basrah Score: a novel machine learning-based score for differentiating iron deficiency anemia and beta thalassemia trait using RBC indices by Salma A. Mahmood, Asaad A. Khalaf, Saad S. Hamadi

“…Traditional discrimination indices—such as the Mentzer Index, Ihsan's formula, and the England and Fraser criteria—have been extensively applied in both research and clinical settings; however, their diagnostic performance varies considerably across different populations and datasets. …”
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Leveraging AI in ayurvedic agriculture: A RAG chatbot for comprehensive medicinal plant insights using hybrid deep learning approaches by Biplov Paneru, Bipul Thapa, Bishwash Paneru

“…The Nepalese and Indian agriculture systems are one of the main areas focusing on medicinal plant cultivation, and the abundant availability of these plants in these regions is driving growth in ayurvedic research. Traditional methods for detecting plants as well as generating insights on them are often inefficient and time-consuming due to the manual research need and expertise required in plant and biological lives. …”
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Enhanced convolutional neural network methodology for solid waste classification utilizing data augmentation techniques by Daniel Hogan Itam, Ekwueme Chimeme Martin, Ibiba Taiwo Horsfall

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Optimizing non small cell lung cancer detection with convolutional neural networks and differential augmentation by Vahiduddin Shariff, Chiranjeevi Paritala, Krishna Mohan Ankala

“…Hyperparameter tuning was performed using Random Search to optimize parameters, further improving performance. …”
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MAOOA‐Residual‐Attention‐BiConvLSTM: An Automated Deep Learning Framework for Global TEC Map Prediction by Haoran Wang, Haijun Liu, Jing Yuan, Huijun Le, Weifeng Shan, Liangchao Li

“…Optimization can help find a better quasi‐optimal hyperparameter combination and improve the performance of the model. …”
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Enhancing student success prediction in higher education with swarm optimized enhanced efficientNet attention mechanism. by Meshari Alazmi, Nasir Ayub

“…The key insights the current research provides are the necessity of early intervention and directed training support in the educational domain. …”
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Enhancing Review Processing in the Video Game Adaptation Domain through VADER and Rating-Based Labeling using SVM by Danita Divka Sajmira, Khothibul Umam, Maya Rini Handayani

“…Integrating VADER labeling with SVM enhances sentiment analysis effectiveness and offers practical value for media analytics, content creation, and audience insight research.…”
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Leveraging hybrid 1D-CNN and RNN approach for classification of brain cancer gene expression by Heba M. Afify, Kamel K. Mohammed, Aboul Ella Hassanien

“…The continuous availability of gene expression datasets over the preceding years has made them one of the most accessible sources of genome-wide data, advancing cancer bioinformatics research and advanced prediction of cancer genomic data. …”
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Morphological Analysis and Subtype Detection of Acute Myeloid Leukemia in High-Resolution Blood Smears Using ConvNeXT by Mubarak Taiwo Mustapha, Dilber Uzun Ozsahin

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Feasibility of EfficientDet-D3 for Accurate and Efficient Void Detection in GPR Images by Sung-Pil Shin, Sang-Yum Lee, Tri Ho Minh Le

“…The model was fine-tuned through hyperparameter optimization, achieving a precision of 91.2%, a recall of 87.5%, and an F1-score of 89.3%. …”
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Enhancing Visual Question Answering for Multiple Choice Questions by Rashi Goel, Harsh Nandwani, Eshaan Shah, Ashalatha Nayak, Archana Praveen Kumar

“…Using MCQs provides the model with some context of the correct answer, improving its performance over a simple multiclass classification task. The research showcases the effectiveness of precise hyperparameter adjustments in improving the performance of VQA systems, through comparative analysis of varied sets of hyperparameters, highlighting their improved reasoning capabilities across various datasets, including samples from real world images and academic questions. …”
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