Randomization-Driven Hybrid Deep Learning for Diabetic Retinopathy Detection by A. M. Mutawa, G. R. Hemalakshmi, N. B. Prakash, M. Murugappan

“…This study pioneers an innovative framework, using Multi-Scale Discriminative Robust Local Binary Pattern (MS-DRLBP) features, combined with a hybrid Convolutional Neural Network-Radial Basis Function (CNN-RBF) classifier, to enhance the detection of DR. …”
Get full text

The spatial–temporal evolution characteristics and influencing factors of coordinated development in the Yellow River Basin: Based on the perspective of flood-sediment transport, e... by Ni Geng, Guiliang Tian, Hengquan Zhang

“…Considering the characteristics of the YRB, we proposed a complex basin-wide analytical framework consisting of FS-EE-SE (FES) system. Firstly, we used the entropy weight method to determine the indicators weights and built the coupling coordination degree (CCD) model. …”
Get full text

Spatiotemporal information conversion machine for time-series forecasting by Hao Peng, Pei Chen, Rui Liu, Luonan Chen

“…In this work, a neural network computing framework, the spatiotemporal information conversion machine (STICM), was developed to efficiently and accurately render a forecasting of a time series by employing a spatial-temporal information (STI) transformation. …”
Get full text

RETRACTED ARTICLE: An intelligent dynamic cyber physical system threat detection system for ensuring secured communication in 6G autonomous vehicle networks by Shanthalakshmi M, Ponmagal R S

“…So we present a novel approach to mitigating these security risks by leveraging pre-trained Convolutional Neural Network (CNN) models for dynamic cyber-attack detection within the cyber-physical systems (CPS) framework of AVs. …”
Get full text

Advanced Diagnosis of Cardiac and Respiratory Diseases from Chest X-Ray Imagery Using Deep Learning Ensembles by Hemal Nakrani, Essa Q. Shahra, Shadi Basurra, Rasheed Mohammad, Edlira Vakaj, Waheb A. Jabbar

“…This robust ensemble learning framework underscores its potential for reliable and precise disease detection, offering significant improvements over traditional methods. …”
Get full text

Multimodal Fusion Mamba Network for Joint Land Cover Classification Using Hyperspectral and LiDAR Data by Haizhu Pan, Ruixiang Zhao, Haimiao Ge, Moqi Liu, Quanxiu Zhang

“…Recently, the emerging deep learning framework Mamba has shown superior performance over traditional architectures, including transformers and convolutional neural networks. …”
Get full text

I-AIR: intention-aware travel itinerary recommendation via multi-signal fusion and spatiotemporal constraints by Xiao Cui, Zhihua Wang, Ping Li, Qiang Xu

“…To address these limitations, we propose an intention-aware deep learning framework that integrates diverse user signals into a unified itinerary planning model. …”
Get full text

Recognition of Handwritten Characters in Birch-Bark Manuscripts via Object Detection by Ivan P. Malashin, Vadim S. Tynchenko, Andrei P. Gantimurov, Vladimir A. Nelyub, Aleksei S. Borodulin

“…This study adapts the YOLO-based object detection framework for detection and recognition of handwritten characters in digital photographs of Novgorod birch-bark fragments. …”
Get full text

Energy-Efficient Secure Cell-Free Massive MIMO for Internet of Things: A Hybrid CNN–LSTM-Based Deep-Learning Approach by Ali Vaziri, Pardis Sadatian Moghaddam, Mehrdad Shoeibi, Masoud Kaveh

“…To enhance SEE, we introduce a hybrid deep-learning (DL) framework that integrates convolutional neural networks (CNN) and long short-term memory (LSTM) networks for joint EE and security optimization. …”
Get full text

Inequalities in Mild Cognitive Impairment Risk Among Chinese Middle-Aged and Older Adults: Insights from an Integrated Learning Model by Bi S, Guo D, Tan H, Chen Y, Li G

“…Shengxian Bi,1 Dandan Guo,2 Huawei Tan,1 Yingchun Chen,1 Gang Li3 1School of Medicine and Health Management, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, 430030, People’s Republic of China; 2School of Public Health and Health Sciences, Hubei University of Medicine, Shiyan, Hubei, 442000, People’s Republic of China; 3School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, People’s Republic of ChinaCorrespondence: Yingchun Chen, School of Medicine and Health Management, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, People’s Republic of China, Email chenyingchunhust@163.com Gang Li, School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, People’s Republic of China, Email ligang2024@sjtu.edu.cnObjective: This study aims to address inequalities in mild cognitive impairment (MCI) risk among Chinese middle-aged and older adults by developing an integrated learning framework to predict MCI risk and identify key contributing factors.Methods: Using CHARLS data of 4626 participants, we developed a convolutional neural network-bidirectional long short-term memory-attention (CNN-BiLSTM-Attention) model to capture the temporal and spatial features of MCI progression. …”
Get full text

Swin Transformer and Momentum Contrast (MoCo) in Leukemia Diagnostics: A New Paradigm in AI-Driven Blood Cell Cancer Classification by Eshika Jain, Pratham Kaushik, Vinay Kukreja, Modafar Ati, Shanmugasundaram Hariharan, Vandana Ahuja, Abhishek Bhattacherjee, Rajesh Kumar Kaushal

“…Despite their widespread use in medical imaging, Convolutional Neural Networks (CNNs) struggle to differentiate morphologically similar ALL subtypes due to limited context and feature discrimination. …”
Get full text

Deep-learning-based sub-seasonal precipitation and streamflow ensemble forecasting over the source region of the Yangtze River by N. Dong, H. Hao, H. Hao, M. Yang, J. Wei, S. Xu, H. Kunstmann, H. Kunstmann, H. Kunstmann

“…We propose a deep-learning-based modelling framework for sub-seasonal joint precipitation and streamflow ensemble forecasts for a lead time of up to 30 d. …”
Get full text

TPDTNet: Two-Phase Distillation Training for Visible-to-Infrared Unsupervised Domain Adaptive Object Detection by Siyu Wang, Xiaogang Yang, Ruitao Lu, Shuang Su, Bin Tang, Tao Zhang, Zhengjie Zhu

“…This convolutional operation is embedded following standard convolution to mitigate the loss of detailed features. …”
Get full text

Deep cascaded registration and weakly-supervised segmentation of fetal brain MRI by Valentin Comte, Mireia Alenya, Andrea Urru, Judith Recober, Ayako Nakaki, Francesca Crovetto, Oscar Camara, Eduard Gratacós, Elisenda Eixarch, Fatima Crispi, Gemma Piella, Mario Ceresa, Miguel A. González Ballester

“…To address this challenge, we introduce a deep learning registration framework comprising multiple cascaded convolutional networks. …”
Get full text

Passive Sensing for Mental Health Monitoring Using Machine Learning With Wearables and Smartphones: Scoping Review by ShiYing Shen, Wenhao Qi, Jianwen Zeng, Sixie Li, Xin Liu, Xiaohong Zhu, Chaoqun Dong, Bin Wang, Yankai Shi, Jiani Yao, Bingsheng Wang, Xiajing Lou, Simin Gu, Pan Li, Jinghua Wang, Guowei Jiang, Shihua Cao

“…Deep learning models (eg, convolutional neural networks and long short-term memory) showed high accuracy, while traditional ML (eg, random forest) remained prevalent due to better interpretability. …”
Get full text

An analytical examination of the performance assessment of CNN-LSTM architectures for state-of-health evaluation of lithium-ion batteries by Arun Jose, Sonam Shrivastava

“…This research specifically examines the potential of the convolutional neural network–long short-term memory algorithm to improve the precision of State of Health forecasts for the battery model. …”
Get full text

Explainable MRI-Based Ensemble Learnable Architecture for Alzheimer’s Disease Detection by Opeyemi Taiwo Adeniran, Blessing Ojeme, Temitope Ezekiel Ajibola, Ojonugwa Oluwafemi Ejiga Peter, Abiola Olayinka Ajala, Md Mahmudur Rahman, Fahmi Khalifa

“…The study explores a few commonly used perturbation-based interpretability (LIME) and gradient-based interpretability (Saliency and Grad-CAM) approaches for visualizing and explaining the dataset, models, and decisions of MRI image-based Alzheimer’s disease identification using the diagnostic and predictive strengths of an ensemble framework comprising Convolutional Neural Networks (CNNs) architectures (Custom multi-classifier CNN, VGG-19, ResNet, MobileNet, EfficientNet, DenseNet), and a Vision Transformer (ViT). …”
Get full text

A two phase ensembled deep learning approach of prominent gene extraction and disease risk prediction by Prajna Paramita DEBATA, Alakananda TRIPATHY, Pournamasi PARHI, Smruti Rekha DAS

“…Therefore, a two phase ensembled deep learning approach can be considered as a dependable framework for the root level investigation of genomic data. …”
Get full text

HistoDX: Revolutionizing Breast Cancer Diagnosis Through Advanced Imaging Techniques by Wishal Arshad, Tehreem Masood, H. M. Shahzad, Hassan A. Ahmed, Syed Hamza Ahmed, Hafiz Muhammad Tayyab Khushi

“…This study introduces HistoDX, a deep learning framework to classify Invasive Ductal Carcinoma (IDC) using 277,524 histopathology image patches (<inline-formula> <tex-math notation="LaTeX">$50\times 50$ </tex-math></inline-formula> pixels) from Paul Mooney&#x2019;s IDC dataset on Kaggle, comprising No Cancer and IDC(+) classes. …”
Get full text

Diagnosis of epileptic seizure neurological condition using EEG signal: a multi-model algorithm by Mosleh Hmoud Al-Adhaileh, Mosleh Hmoud Al-Adhaileh, Sultan Ahmad, Alhasan A. Alharbi, Mohammed Alarfaj, Mohammed Alarfaj, Mukta Dhopeshwarkar, Theyazn H. H. Aldhyani

“…The EEG data classification by applying ML and DL framework to improve the accuracy of seizure detection. …”
Get full text