Enhancing Autism Spectrum Disorder Classification with Lightweight Quantized CNNs and Federated Learning on ABIDE-1 Dataset by Simran Gupta, Md. Rahad Islam Bhuiyan, Sadia Sultana Chowa, Sidratul Montaha, Rashik Rahman, Sk. Tanzir Mehedi, Ziaur Rahman

“…Initially, the Regions of Interest (ROIs) are converted into feature vectors using tangent space embedding to feed into the Q-CNN model. …”
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Multi-label semantic segmentation of magnetic resonance images of the prostate gland by Mark Locherer, Christopher Bonenberger, Wolfgang Ertel, Boris Hadaschik, Kristina Stumm, Markus Schneider, Jan Philipp Radtke

“…The performance of the presented methodology is compared and evaluated using the dice score metric and 5-fold cross-validation on all datasets. …”
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Multistep Brent oil price forecasting with a multi-aspect meta-heuristic optimization and ensemble deep learning model by Mohammed Alruqimi, Luca Di Persio

“…Unlike existing methods that apply metaheuristics to optimise hyperparameters within the neural network architecture, we exploit the GWO metaheuristic optimiser at four levels: feature selection, data preparation, model training, and forecast blending. …”
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Prediction of Temperature Distribution with Deep Learning Approaches for SM1 Flame Configuration by Gökhan Deveci, Özgün Yücel, Ali Bahadır Olcay

“…The second framework employs a U-Net-based convolutional neural network enhanced by an RGB Fusion preprocessing technique, which integrates multiple scalar fields from non-reacting (cold flow) conditions into composite images, significantly improving spatial feature extraction. …”
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Emotion-Aware Embedding Fusion in Large Language Models (Flan-T5, Llama 2, DeepSeek-R1, and ChatGPT 4) for Intelligent Response Generation by Abdur Rasool, Muhammad Irfan Shahzad, Hafsa Aslam, Vincent Chan, Muhammad Ali Arshad

“…Therapy session transcripts, comprising over 2000 samples, are segmented into hierarchical levels (word, sentence, and session) using neural networks, while hierarchical fusion combines these features with pooling techniques to refine emotional representations. …”
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Integrative bioinformatics and machine learning identify key crosstalk genes and immune interactions in head and neck cancer and Hodgkin lymphoma by Meiling Qin, Xinxin Li, Xun Gong, Yuan Hu, Min Tang

“…The intersection of HNSCC DEGs and HL-related modules was evaluated using protein–protein interaction (PPI) network analysis. …”
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Enhanced Occupational Safety in Agricultural Machinery Factories: Artificial Intelligence-Driven Helmet Detection Using Transfer Learning and Majority Voting by Simge Özüağ, Ömer Ertuğrul

“…A transfer learning approach was employed, utilizing nine pre-trained neural networks for the extraction of deep features. The following neural networks were employed: MobileNetV2, ResNet50, DarkNet53, AlexNet, ShuffleNet, DenseNet201, InceptionV3, Inception-ResNetV2, and GoogLeNet. …”
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An Explainable Artificial Intelligence Text Classifier for Suicidality Prediction in Youth Crisis Text Line Users: Development and Validation Study by Julia Thomas, Antonia Lucht, Jacob Segler, Richard Wundrack, Marcel Miché, Roselind Lieb, Lars Kuchinke, Gunther Meinlschmidt

“…ObjectiveThis study aimed to (1) develop and implement ML methods for predicting SIBs in a real-world crisis helpline dataset, using transformer-based pretrained models as a foundation; (2) evaluate, cross-validate, and benchmark the model against traditional text classification approaches; and (3) train an explainable model to highlight relevant risk-associated features. …”
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Incidence, clinical and genomic trends of hospital- and Non-hospital-onset KPC-producing Klebsiella pneumoniae infections before and during the COVID-19 era: a ten-year interrupted... by Manuel Recio-Rufián, Teresa López-Viñau, Víctor Gálvez-Soto, Ángela Cano, Rafael Ruiz-Montero, Belén Gutiérrez-Gutiérrez, Irene Gracia-Ahufinger, Germán Peñalva, Juan Antonio Marín-Sanz, Miriam Marín-Sanz, David Segorbe, Juan Jesús Pineda-Capitán, Montserrat Muñoz-Rosa, Cristina Riazzo, Federico Giovagnorio, Elisa Ruiz-Arabi, José David Torres-Peña, Juan José Castón, Isabel Machuca, Inmaculada Salcedo-Leal, Luis Martínez-Martínez, Elena Pérez-Nadales, Julián Torre-Cisneros, KLEBMAN study group

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Securing IoT-Cloud Applications with AQ-KGMO-DMG Enhanced SVM for Intrusion Detection by Konduru Siva Naga Narasimharao, P. V. Lakshmi

“…In this work, a pioneering network intrusion detection model is introduced, leveraging Adaptive Quantum-Inspired KGMO with Dynamic Molecular Grouping (AQ-KGMO-DMG) for feature selection and employing Simplified Support Vector Machines (SVM) for the classification of intrusion data. …”
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Identify suitable artificial groundwater recharge zones using hybrid deep learning models by Navaz Khalillollahi, Mohsen Isari, Hamed Faroqi, Kaywan Othman Ahmed, Kamran Nobakht Vakili, Miklas Scholz, Saad Sh. Sammeng

“…Identifying groundwater recharge zones is crucial for sustainable water resource management in water-scarce environments, such as Kurdistan, Iran. This study evaluated four deep learning models for delineating groundwater recharge zones: Artificial Neural Network (ANN), Convolutional Neural Network (CNN), Gated Recurrent Unit (GRU), and hybrid deep learning Convolutional Neural Network-Gated Recurrent Unit (CNN-GRU). …”
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Automatic Potato Crop Beetle Recognition Method Based on Multiscale Asymmetric Convolution Blocks by Jingjun Cao, Xiaoqing Xian, Minghui Qiu, Xin Li, Yajie Wei, Wanxue Liu, Guifen Zhang, Lihua Jiang

“…This solution is in the form of a new convolutional neural network architecture, known as MSAC-ResNet. Specifically, it comprises several multiscale asymmetric convolution blocks, which are designed to extract features at multiple scales, mainly by integrating different-sized asymmetric convolution kernels in parallel. …”
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Identification of anoikis-related subtypes and a risk score prognosis model, the association with TME landscapes and therapeutic responses in hepatocellular carcinoma by Xiangyu Zhai, Xiangyu Zhai, Kecheng Li, Hailing Ding, Yanmei Wu, Xinlu Zhang, Hao Zhang, Huaxin Zhou, Huaxin Zhou, Chongzhong Liu, Zili Zhang, Bin Jin, Bin Jin

“…Weighted Gene Co-expression Network Analysis (WGCNA) identified hub gene modules, and LASSO Cox regression was applied to construct a prognostic risk score model. …”
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A survey of data-driven fault-diagnosis methods for large-scale industrial production processes by Qianxiang YU, Qing LI, Linlin LI, Yixuan WANG

“…The latest advances in system decomposition and data fusion, correlation analysis, and consensus mechanisms are elaborated on subsystems based on the distributed structure and sensor networks in large-scale systems. System decomposition focuses on the local features of each subsystem although adopting a purely subsystem-centric approach to data processing often leans toward decentralization, in contrast to the essence of distribution. …”
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Mobile health (mHealth) interventions for health promotion during the perinatal period in India: a scoping review by Zara Small, Sophie Elizabeth Thompson, Ankita Sharma, Sreya Majumdar, Sudhir Raj Thout, Devarsetty Praveen, Devarsetty Praveen, Devarsetty Praveen, Jane Elizabeth Hirst, Jane Elizabeth Hirst

“…However, current interventions lack evidence of long term behavioural change and fail to report on features important in sustainability and scalability, namely network infrastructure, data security and interoperability. …”
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Sturge Weber syndrome in a multinational pediatric cohort: a systematic analysis of different types by Sigrid Disse, Georgia Ramantani, Hanna Küpper, Annette Bock, Georg-Christoph Korenke, Birgit Weidner, Martin Preisel, Regina Trollmann, Adelheid Wiemer-Kruel, Sven Wellmann, Knut Brockmann, Simone Schroeder, Sascha Meyer

“…Only few patients were evaluated for surgery, despite uncontrolled, structural epilepsy. …”
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Deep-learning prediction of cardiovascular outcomes from routine retinal images in individuals with type 2 diabetes by Mohammad Ghouse Syed, Emanuele Trucco, Muthu R. K. Mookiah, Chim C. Lang, Rory J. McCrimmon, Colin N. A. Palmer, Ewan R. Pearson, Alex S. F. Doney, Ify R. Mordi

“…Abstract Background Prior studies have demonstrated an association between retinal vascular features and cardiovascular disease (CVD), however most studies have only evaluated a few simple parameters at a time. …”
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Deep learning assisted analysis of biomarker changes in refractory neovascular AMD after switch to faricimab by Michael Hafner, Franziska Eckardt, Jakob Siedlecki, Benedikt Schworm, Tina R. Herold, Ben Asani, Siegfried G. Priglinger, Johannes B. Schiefelbein

“…Abstract Background Artificial intelligence (AI)-driven biomarker segmentation offers an objective and reproducible approach for quantifying key anatomical features in neovascular age-related macular degeneration (nAMD) using optical coherence tomography (OCT). …”
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Application of Mask R-CNN for automatic recognition of teeth and caries in cone-beam computerized tomography by Yujie Ma, Maged Ali Al-Aroomi, Yutian Zheng, Wenjie Ren, Peixuan Liu, Qing Wu, Ye Liang, Canhua Jiang

“…Abstract Objectives Deep convolutional neural networks (CNNs) are advancing rapidly in medical research, demonstrating promising results in diagnosis and prediction within radiology and pathology. …”
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Blood glucose level prediction in type 1 diabetes: A comparative analysis of interpretable artificial intelligence approaches by Ilaria Basile, Giovanna Sannino

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