Forecasting the daily evaporation by coupling the ensemble deep learning models with meta-heuristic algorithms and data pre-processing in dryland by Tonglin Fu, Dong Wang, Jing Jin

“…To achieve this purpose, the Convolutional neural network (CNN) was integrated with Bidirectional long short-term memory network (BiLSTM) as main estimating module, and the Sparrow search algorithm (SSA) was employed to search the optimal hyperparameters of CNN-BiLSTM. …”
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Automatic detecting multiple bone metastases in breast cancer using deep learning based on low-resolution bone scan images by Jialin Shi, Ruolin Zhang, Zongyao Yang, Zhixian Chen, Zhixin Hao, Li Huo, Ji Wu, Qiang Sun, Yali Xu

“…Experiments were conducted to evaluate the effectiveness of our method. First, compared to different network architectures, our method obtained AP of 55.0 ± 6.4% (95% confidence intervals (CI) 49.9–60.1%, $$p<0.05$$ ), which improved AP by 45.2% for the SSD baseline with AP 9.8 ± 2% (95% CI 8.1–11.4%). …”
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Linguistic Markers of Pain Communication on X (Formerly Twitter) in US States With High and Low Opioid Mortality: Machine Learning and Semantic Network Analysis by ShinYe Kim, Winson Fu Zun Yang, Zishan Jiwani, Emily Hamm, Shreya Singh

“…ObjectiveThis study aimed to examine linguistic markers of pain communication on the social media platform X and assess whether language patterns differ among US states with high and low opioid mortality rates. We also evaluated the predictive power of these linguistic features using machine learning and identified key thematic structures through semantic network analysis. …”
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Analysis of Bladder Cancer Staging Prediction Using Deep Residual Neural Network, Radiomics, and RNA-Seq from High-Definition CT Images by Yao Zhou, Xingju Zheng, Zhucheng Sun, Bo Wang

“…This study focuses on evaluating the potential of high-definition computed tomography (CT) imagery coupled with RNA-sequencing analysis to accurately predict bladder tumor stages, utilizing deep residual networks. …”
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Benchmarking CNN Architectures for Tool Classification: Evaluating CNN Performance on a Unique Dataset Generated by Novel Image Acquisition System by Muhenad Bilal, Ranadheer Podishetti, Daniel Grossmann, Markus Bregulla

“…It is compared with conventional diffuse ring illumination to assess its effectiveness in evaluating state-of-the-art convolutional neural networks. …”
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PM2.5 prediction and its influencing factors in the Beijing-Tianjin-Hebei urban agglomeration using spatial temporal graph convolutional networks by Yawen Zhao

“…To address this, this study uses spatiotemporal analysis and Spatial Temporal Graph Convolutional Networks (ST-GCN) to evaluate the variation and driving factors of PM _2.5 concentrations in the Beijing-Tianjin-Hebei (BTH) urban agglomeration from 2014 to 2024, and to make predictions. …”
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An Improved Decision Support System for Identification of Abnormal EEG Signals Using a 1D Convolutional Neural Network and Savitzky-Golay Filtering by Unmesh Shukla, Geetika Jain Saxena, Manish Kumar, Anil Singh Bafila, Amit Pundir, Sanjeev Singh

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CN2VF-Net: A Hybrid Convolutional Neural Network and Vision Transformer Framework for Multi-Scale Fire Detection in Complex Environments by Naveed Ahmad, Mariam Akbar, Eman H. Alkhammash, Mona M. Jamjoom

“…This paper proposes the CN2VF-Net model, a novel hybrid architecture that combines vision Transformers (ViTs) and convolutional neural networks (CNNs), effectively addressing these challenges. …”
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Short-term prediction of storm surges in estuarine and coastal waters via a multipoint deep learning neural network with limited training samples by Zhuo Zhang, Lu Zhang, Songshan Yue, Dong Zhang, Zhaoyuan Yu, Di Hu, Peng Chen

“…Unlike traditional single-point neural network models that focus on individual tide stations, this study introduces multipoint models and incorporates a convolutional layer to extract spatial features from tide levels at neighboring stations. …”
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RED-Net: A Neural Network for 3D Thyroid Segmentation in Chest CT Using Residual and Dilated Convolutions for Measuring Thyroid Volume by Min-Ji Kim, Jin-A Kim, Naae Kim, Yul Hwangbo, Hyun Jeong Jeon, Dong-Hwa Lee, Ji Eun Oh

“…We designed a residual and dilated convolution neural network (RED-Net), which automatically measures thyroid volume by segmenting the thyroid gland in contrast-enhanced chest CT scans. …”
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A Temporal Convolutional Network–Bidirectional Long Short-Term Memory (TCN-BiLSTM) Prediction Model for Temporal Faults in Industrial Equipment by Jinyin Bai, Wei Zhu, Shuhong Liu, Chenhao Ye, Peng Zheng, Xiangchen Wang

“…To address these issues, this paper proposes a combined prediction model based on an improved temporal convolutional network (TCN) and bidirectional long short-term memory (BiLSTM), referred to as the TCN-BiLSTM model. …”
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Lightweight convolutional neural networks using nonlinear Lévy chaotic moth flame optimisation for brain tumour classification via efficient hyperparameter tuning by Amin Abdollahi Dehkordi, Mehdi Neshat, Alireza Khosravian, Menasha Thilakaratne, Ali Safaa Sadiq, Seyedali Mirjalili

“…Abstract Deep convolutional neural networks (CNNs) have seen significant growth in medical image classification applications due to their ability to automate feature extraction, leverage hierarchical learning, and deliver high classification accuracy. …”
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BlockDroid: detection of Android malware from images using lightweight convolutional neural network models with ensemble learning and blockchain for mobile devices by Emre Şafak, İbrahim Alper Doğru, Necaattin Barışçı, İsmail Atacak

“…This article presents BlockDroid, an approach that combines convolutional neural network (CNN) models, ensemble learning, and blockchain technology to increase the accuracy and efficiency of malware detection for mobile devices. …”
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Prospective Evaluation of the Pathologic Diagnosis and Treatment Outcomes of Pediatric Burkitt Lymphoma in the Central American Pediatric Hematology-Oncology Association Consortium by Priya Kumar, Monika L. Metzger, John K. Choi, Godwin Job, Teresa C. Santiago, Armando Peña, Miguela A. Caniza, Asya Agulnik, Pascale Y. Gassant, Wendy C. Gómez García, Patricia J. Calderón, Claudia Garrido, Roy Rosado, Soad Fuentes Alabí, Valentino Conter, Meenakshi Devidas, Angela K. Carrillo, Yichen Chen, Paola Friedrich, Carlos Rodriguez Galindo, Guillermo L. Chantada, Victor M. Santana

“…The concordance of sample assessments was evaluated using three criteria: histologic diagnosis, morphology, and immunohistochemistry. …”
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MM-3D Unet: development of a lightweight breast cancer tumor segmentation network utilizing multi-task and depthwise separable convolution by Xian Wang, Wenzhi Zeng, Junzeng Xu, Senhao Zhang, Yuexing Gu, Benhui Li, Xueyang Wang

“…In addition, an auxiliary classification task (ACT) is introduced in the proposed architecture to provide additional supervisory signals for the main task of segmentation. The network architecture features a contracting path for downsampling and an expanding path for precise localization, enhanced by skip connections that integrate multi-level semantic information.ResultsThe network was evaluated using a dataset of Dynamic Contrast Enhanced MRI (DCE-MRI) breast cancer images, and the results show that compared to the classical 3DU-Net, MM-3DUNet could significantly reduce model parameters by 63.16% and computational demands by 80.90%, while increasing segmentation accuracy by 1.30% in IoU (Intersection over Union).ConclusionsMM-3DUNet offers a substantial reduction in computational requirements of breast cancer mass segmentation network. …”
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Deep Learning Approach for Classifying DDoS Attack Traffic in SDN Environments by Mohd Nadeem, Shweta Dwivedi, Rizwan Akhtar, Shameem Ahmad Ansari, Saumya Singh, Eram Fatima Siddiqui, Rajeev Kumar

“…DDoS assaults, including SYN, UDP, and ICMP floods, pose significant risks by overloading network capacity and disrupting normal operations. …”
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TS2GNet: A temporal–spatial–spectral multidomain guided network for classifying hyperspectral tree species using multiseason satellite imagery by Kaijian Xu, Henghui Han, Shuzhou Wang, Ping Zhao, Jun Geng, Hailan Jiang, Anxin Ding

“…TS2GNet employs a dual-stream architecture that focus on dynamic interactions between spatial and spectral domains, while also incorporating temporal modeling and SHSI feature-domain guidance. We evaluate our method on eight dominant tree species in the Ta-pieh Mountains and compare its performance with six state-of-the-art (SOTA) deep learning-based hyperspectral classification methods. …”
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CPS-IIoT-P2Attention: Explainable Privacy-Preserving With Scaled Dot-Product Attention in Cyber-Physical System-Industrial IoT Network by Yakub Kayode Saheed, Joshua Ebere Chukwuere

“…These mechanisms adaptively modify their emphasis to prioritize crucial features within the CPS-IIoT network traffic data, providing additional computational resources to data segments that are likely to include abnormalities and patterns that indicate security issues. …”
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Advanced AI techniques for classifying Alzheimer’s disease and mild cognitive impairment by Sophie Tascedda, Sophie Tascedda, Sophie Tascedda, Pierfrancesco Sarti, Pierfrancesco Sarti, Veronica Rivi, Claudia Savia Guerrera, Giuseppe Alessio Platania, Mario Santagati, Filippo Caraci, Filippo Caraci, Johanna M. C. Blom, Johanna M. C. Blom

“…This issue underscores the necessity for improved diagnostic techniques to better identify cognitive disorders in the aging population.MethodsWe used Graph Neural Networks, Multi-Layer Perceptrons, and Graph Attention Networks. …”
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Improving the prediction of streamflow in large watersheds based on seasonal trend decomposition and vectorized deep learning models by Ningchang Kang, Zhaocai Wang, Anbin Zhang, Hang Chen

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