Downscaling of Soil Moisture Map using Sentinel Radar Satellite Images and Distribution Analysis in the West of Iran by Seyed Hossein Mirmosavi, kohzad Raispour, Muhammad Kamangar

“…The micro-scale backup machine vector algorithm and the high volume resolution soil moisture dispersion map were estimated between 0.18 and 0.46 b. …”
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TATPat based explainable EEG model for neonatal seizure detection by Turker Tuncer, Sengul Dogan, Irem Tasci, Burak Tasci, Rena Hajiyeva

“…In this EFE model, there are four essential phases and these phases: (i) automaton and transformer-based feature extraction, (ii) feature selection deploying cumulative weight-based neighborhood component analysis (CWNCA), (iii) the Directed Lobish (DLob) and Causal Connectome Theory (CCT)-based explainable result generation and (iv) classification deploying t algorithm-based support vector machine (tSVM). In the first phase, we have used a channel transformer to get channel numbers and these values have been divided into three levels and these levels are named (1) high, (2) medium and (3) low. …”
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Dataset creation of thermal images of pomegranate for internal defect detectionMendeley Data by Ashvini Gaikwad, Manoj Deshpande, Varsha Bhole

“…This information is useful for training a machine learning algorithms that are intended for bulk processing in the field of fruit defect detection and classification.…”
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Research and analysis of differential gene expression in CD34 hematopoietic stem cells in myelodysplastic syndromes. by Min-Xiao Wang, Chang-Sheng Liao, Xue-Qin Wei, Yu-Qin Xie, Peng-Fei Han, Yan-Hui Yu

“…After comprehensive evaluation, we ultimately selected three algorithms-Lasso regression, random forest, and support vector machine (SVM)-as our core predictive models. …”
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A predictive analytics framework for opportunity sensing in stock market by Shruti Mittal, C.K. Nagpal

“…Thus research papers in this area suffer from multiple limitations: Very short prediction period from one day to one week, consideration of few stocks only instead of whole of stock market spectrum, exploration of more suitable machine learning algorithms. By overcoming the problems of raw data these limitations can be conquered. …”
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Unsupervised Learning for Heart Disease Prediction: Clustering-Based Approach by Jetty Janani., Sk Sajida Sultana., Polepalle Ranga Bhavitha., Parusu Vishwitha.

“…This paper on the prediction of heart disease addresses the application of unsupervised machine learning algorithms, digs up the latent pattern of risk in the data of patients for early diagnosis, and intervenes. …”
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Artificial intelligence-based Raynaud’s quantification index (ARTIX): an objective mobile-based tool for patient-centered assessment of Raynaud’s phenomenon by Marco Di Battista, Seda Colak, Anna Howard, Francesca Donadoni, Chris Owen-Smith, Andrea Rindone, Stefano Di Donato, Collette Hartley, Lesley-Anne Bissell, Francesco Del Galdo

“…Abstract Background We aimed to develop an artificial intelligence algorithm able to assess Raynaud’s phenomenon (RP) from mobile phone photography, ensuring as a patient-centered, image-based method for RP quantification. …”
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Beyond human-in-the-loop: Sensemaking between artificial intelligence and human intelligence collaboration by Xinyue Hao, Emrah Demir, Daniel Eyers

“…While AI contributes speed, scale, and pattern recognition in routine, structured environments, human actors provide ethical oversight, contextual judgment, and strategic interpretation, particularly vital in uncertain or ethically charged contexts. …”
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Luminescence-enabled three-dimensional temperature bioimaging by Liyan Ming, Anna Romelli, José Lifante, Patrizia Canton, Ginés Lifante-Pedrola, Daniel Jaque, Erving Ximendes, Riccardo Marin

“…The optimized neural network-based algorithm can extract this information and provide 3D thermal images of complex nanothermometer patterns. …”
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Assessing the Accuracy and Consistency of Cropland Datasets and Their Influencing Factors on the Tibetan Plateau by Fuyao Zhang, Xue Wang, Liangjie Xin, Xiubin Li

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Strategies and Challenges in Detecting XSS Vulnerabilities Using an Innovative Cookie Collector by Germán Rodríguez-Galán, Eduardo Benavides-Astudillo, Daniel Nuñez-Agurto, Pablo Puente-Ponce, Sonia Cárdenas-Delgado, Mauricio Loachamín-Valencia

“…Additionally, clustering algorithms enabled user segmentation based on cookie data, identification of behavioral patterns, enhanced personalized web recommendations, and browsing experience optimization. …”
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Fog Computing and Industry 4.0 for Newsvendor Inventory Model Using Attention Mechanism and Gated Recurrent Unit by Joaquin Gonzalez, Liliana Avelar Sosa, Gabriel Bravo, Oliverio Cruz-Mejia, Jose-Manuel Mejia-Muñoz

“…<i>Methods</i>: To address these challenges, our study introduces a system that incorporates a machine learning algorithm to address inventory-related uncertainties arising from demand fluctuations. …”
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A multimodal approach for ADHD with coexisting ASD detection for children by Jungpil Shin, Sota Konnai, Md. Maniruzzaman, Yoichi Tomioka, Yong Seok Hwang, Akiko Megumi, Akira Yasumura

“…The potentiality of these features was evaluated using Sequential Forward Floating Selection (SFFS)-based algorithm and support vector machine (SVM) was employed to evaluate the performance of ZL and PL tasks. …”
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Comprehensive analysis of mRNA and lncRNA expression for predicting lymph node metastasis in cervical cancer: a novel seven-gene signature approach by Jiahui Wei, Ming Wang, Yumei Wu

“…The differential expression of mRNAs and lncRNAs was identified using DESeq2. Subsequently, dual machine learning strategies—LASSO regression and the Boruta algorithm—were applied to select robust biomarkers. …”
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PFVnet, a feature enhancement network for low recognition coal and rock images by Cai Han, Zhenwen Liu, Shenglei Zhao, Yubo Li, Yanwei Duan, Xinzhou Yang, Chuanbo Hao

“…We characterized the grayscale and texture feature patterns of coal-rock media under varying degrees of interference and established a comprehensive multi-element image training sample library. …”
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Hierarchical genetic structure in an evolving species complex: Insights from genome wide ddRAD data in Sebastes mentella. by Atal Saha, Matthew Kent, Lorenz Hauser, Daniel P Drinan, Einar E Nielsen, Jon-Ivar Westgaard, Sigbjørn Lien, Torild Johansen

“…We identified a SNP panel with only 21 loci to discriminate populations in mixed samples based on a machine-learning algorithm. This first SNP based investigation clarifies the population structure of S. mentella, and provides novel and high-resolution genomic tools for future investigations. …”
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The impact of artificial intelligence on financial auditing: the case of Algeria by Amira Benachour, Ramzi Kaddai, Hanane Abdelmalek, Fella Bochelgoum, Lamine Tarhlissia

“…It enables auditors to go beyond the limits of manual analysis, facilitating more accurate and data-driven decisions. AI algorithms can analyze vast volumes of transactions to detect anomalies that may indicate fraud, such as duplications, unexplained discrepancies, or unusual transaction patterns. …”
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Smart indoor monitoring for disabled individuals using an ensemble of deep learning models in an IoT environment by Faisal S. Alsubaei, Abdulrahman A. Alshdadi, Mohammed Rizwanullah

“…These models utilize numerous technologies and sensors to monitor day-to-day work like movement, medication adherence, and sleep patterns, and provide valued perceptions of the user’s everyday life and entire health. …”
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DBSCAN-PCA-INFORMER-Based Droplet Motion Time Prediction Model for Digital Microfluidic Systems by Zhijie Luo, Bin Zhao, Wenjin Liu, Jianhua Zheng, Wenwen Chen

“…As chip usage frequency rises, device degradation introduces seasonal and trend patterns in droplet motion time data, complicating predictive modeling. …”
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Integrated Platform for Bio-Image Processing and Identification of Cervical Cancer by Larisa-Dalina LAZĂR, Diogen BABUC, Todor IVAŞCU

“…Following this, the cervical cells are segmented and classified using a combination of machine learning algorithms, such as shallow machine learning models and Convolutional Neural Networks (CNN). …”
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