Machine learning classification meets migraine: recommendations for study evaluation by Igor Petrušić, Andrej Savić, Katarina Mitrović, Nebojša Bačanin, Gabriele Sebastianelli, Daniele Secci, Gianluca Coppola

“…Abstract The integration of machine learning (ML) classification techniques into migraine research has offered new insights into the pathophysiology and classification of migraine types and subtypes. …”
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Development of deep learning models for high-resolution exposome mapping and health impact assessment by Lan Luan, Zhu Daoyu

“…Traditional exposome mapping methods often face limitations, such as low spatial-temporal resolution, challenges in integrating multi-modal data sources, and inadequate handling of uncertainties in exposure quantification.MethodsTo address these gaps, we introduce an innovative framework that leverages advanced deep learning techniques, adaptive optimization strategies, and multi-scale data integration to achieve high-resolution exposome modeling. …”
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A Cross-Layer Secure and Energy-Efficient Framework for the Internet of Things: A Comprehensive Survey by Rashid Mustafa, Nurul I. Sarkar, Mahsa Mohaghegh, Shahbaz Pervez

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FINE-TUNING RESNET50V2 WITH ADAMW AND ADAPTIVE TRANSFER LEARNING FOR SONGKET CLASSIFICATION IN LOMBOK by Erfan Wahyudi, Bahtiar Imran, Zaeniah, Surni Erniwati, Muh Nasirudin Karim, Zumratul Muahidin

“…The model was trained with data augmentation techniques, including rotation, shifting, and zooming, to increase data diversity. …”
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Methodological approaches to identifying and mapping fields of specific crops on a basis of high-resolution satellite images using phenological, geographic, and regional statistica... by Alexey Unagaev, Irina Korotkova, Natalia Efremova

“…This complicates the reliable identification of the target crops based solely on vegetation index patterns. This research paper aims to investigate the potential of advanced techniques for crop mapping using satellite data and qualitative information. …”
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Obesity Biomarkers: Exploring Factors, Ramification, Machine Learning, and AI‐Unveiling Insights in Health Research by Ankita Awari, Deepika Kaushik, Ashwani Kumar, Emel Oz, Kenan Çadırcı, Charles Brennan, Charalampos Proestos, Mukul Kumar, Fatih Oz

“…Specifically, it explores how ML techniques can process complex data sets to enhance the discovery and validation of biomarkers. …”
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Decoding ISO 19650 Through Process Modelling for Information Management and Stakeholder Communication in BIM by Fonbeyin Henry Abanda, Bharathi Balu, Selorm Emmanuel Adukpo, Adeyemi Akintola

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An equity-based spatial analytics framework for evaluating pharmacy accessibility using geographical information systems by Sara Al-Naabi, Noura Al Nasiri, Talal Al-Awadhi, Meshal Abdullah, Ammar Abulibdeh

“…In Oman, rapid development since the 1970s has led to a focus on the equitable distribution of public services. This research aims to evaluate the spatial accessibility and distribution of pharmacies in Muscat Governorate, Oman, using Geographical Information Systems (GIS) and spatial analysis techniques. …”
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Human inspired deep learning to locate and classify terrestrial and arboreal animals in thermal drone surveys by Kal Backman, Jared Wood, Maquel Brandimarti, Chad T. Beranek, Adam Roff

“…Abstract Drones are an effective tool for animal surveys, capable of generating an abundance of high‐quality ecological data. However, the large volume of ecological data generated introduces an additional problem of the requisite human resources to process and analyse such data. …”
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Enhanced Fetal Arrhythmia Classification by Non-Invasive ECG Using Cross Domain Feature and Spatial Differences Windows Information by Gede Angga Pradipta, Putu Desiana Wulaning Ayu, Made Liandana, Dandy Pramana Hostiadi

“…Finally, we applied oversampling techniques to address the issue of imbalanced data. …”
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Multisource Topographic-Enhanced Cloud Removal for Remote Sensing in Mountainous Landscapes by Meryeme Boumahdi, Consuelo Gonzalo-Martin, Mario Lillo-Saavedra, Marcelo Somos-Valenzuela, Angel Garcia-Pedrero

“…By integrating synthetic aperture radar Sentinel-1 (S1) data, DEM information, and topographic insights into Sentinel-2 (S2) data, our model aims to enhance cloud removal capabilities, particularly in challenging terrains characterized by thick cloud coverage and significant elevation variations. …”
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Association between insecticide exposomics and cognitive function in older adults: an observational study based on NHANES 2011–2014 by Mengfan Zhang, Xiaofang Guo, Yuanjun Chen, Xinghua Liu, Xingdong Lin

“…ObjectiveThis study aims to investigate the association between exposure to insecticide exposomics and cognitive function, among adults aged 60 and above.MethodsWe employed a multi-stage probability sampling method to analyze data derived from the National Health and Nutrition Examination Survey (NHANES) conducted between 2011 and 2014. …”
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Advances and applications of empirical mode decomposition and its variants in hydrology: A review by CHEN Yunfei, LIU Zuyu, LIU Xiuhua, HE Junqi, ZHENG Ce, MA Yandong

“…Effectively extracting and analyzing hidden information, while understanding temporal variation in hydrological data, remains a challenge. Empirical Mode Decomposition (EMD) has garnered increasing attention due to its ability to analyze non-linear and non-stationary data. …”
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Identification of Genetic Variants Based on Single Nucleotide Polymorphisms and Insertion-Deletion Events in TLR8, IRF10b, and GAPDH Genes Related to the Immune System in Rainbow T... by Najmeh Fazeli Moghadam, Ghodrat Rahimi Miyanji, Ayoub Farhadi, Ardeshir Nejati Jawarami, Elham Younesi Melardi

“…The present study aimed to identify genetic variants based on SNP and InDel occurrence using transcriptomic data in some genes expressed in rainbow trout treated with the VHS virus. …”
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<tt>HJ-BIPLOT</tt>: A Theoretical and Empirical Systematic Review of Its 38 Years of History, Using Text Mining and LLMs by Roberto Cascante-Yarlequé, Purificación Galindo-Villardón, Fabricio Guevara-Viejó, José Luis Vicente-Villardón, Purificación Vicente-Galindo

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Discussing the spectrum of physics-enhanced machine learning: a survey on structural mechanics applications by Marcus Haywood-Alexander, Wei Liu, Kiran Bacsa, Zhilu Lai, Eleni Chatzi

“…The intersection of physics and machine learning has given rise to the physics-enhanced machine learning (PEML) paradigm, aiming to improve the capabilities and reduce the individual shortcomings of data- or physics-only methods. …”
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An approach for classifying sociotechnical attacks by Oleksandr Korchenko, Anna Korchenko, Serhii Zybin, Kyrylo Davydenko

“…The development of information technology and data exchange creates new threats to cyber security, including cyber attacks and frauds. …”
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Evaluation of the total contents and bioaccessible fractions of inorganic constituents in nutritive flours exposed to consumption in Brazil by Thaís Luz de Souza, Leilane Rodrigues Santos, Caio Silva Assis Felix, Laura Beatriz Souza e Souza, Ivana Ferreira Simões, Crislaine Santos Lima, Marcele Catarino Souza dos Santos, Rennan Geovanny Oliveira Araújo, Aníbal de Freitas Santos Júnior, Daniele Cristina Muniz Batista Santos

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Integration of UAV Multispectral Remote Sensing and Random Forest for Full-Growth Stage Monitoring of Wheat Dynamics by Donghui Zhang, Hao Qi, Xiaorui Guo, Haifang Sun, Jianan Min, Si Li, Liang Hou, Liangjie Lv

“…The results of this study highlight how innovative monitoring techniques, such as UAV-based multispectral imaging, can significantly improve agricultural practices by providing precise, real-time data on crop growth. …”
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A comprehensive review of deep learning approaches for rice disease detection: Datasets, methodologies, and future directions by Usman Idris Ismail, Hui Na Chua, Rosdiadee Nordin, Muhammed Kabir Ahmed

“…This process has prompted the adoption of automated techniques that integrate deep learning (DL) vision techniques to improve detection accuracy and efficiency. …”
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