Deep Learning Spinal Cord Segmentation Based on B0 Reference for Diffusion Tensor Imaging Analysis in Cervical Spondylotic Myelopathy by Shuoheng Yang, Ningbo Fei, Junpeng Li, Guangsheng Li, Yong Hu

“…Furthermore, a deep-learning-based model, named SCS-Net (Spinal Cord Segmentation Network), was proposed accordingly. The model applies a classical U-shaped architecture with a lightweight feature extraction module, which can effectively alleviate the training data scarcity problem. …”
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An LLM-based hybrid approach for enhanced automated essay scoring by John Atkinson, Diego Palma

“…However, these approaches neglect crucial factors like text structure and semantics, resulting in limited evaluations of coherence and quality. To address these limitations, we propose a hybrid approach to AES that combines multiple features from different linguistic levels. …”
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Spatial mapping of the brain metabolome lipidome and glycome by Harrison A. Clarke, Xin Ma, Cameron J. Shedlock, Terrymar Medina, Tara R. Hawkinson, Lei Wu, Roberto A. Ribas, Shannon Keohane, Sakthivel Ravi, Jennifer L. Bizon, Sara N. Burke, Jose Francisco Abisambra, Matthew E. Merritt, Boone M. Prentice, Craig W. Vander Kooi, Matthew S. Gentry, Li Chen, Ramon C. Sun

“…This workflow integrates a computational platform, the Spatial Augmented Multiomics Interface (Sami), which enables multiomics integration, high-dimensional clustering, spatial anatomical mapping of matched molecular features, and metabolic pathway enrichment. To demonstrate the utility of this approach, we applied Sami to evaluate metabolic diversity across distinct brain regions and to compare wild-type and Ps19 Alzheimer’s disease (AD) mouse models. …”
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Deep Learning-Based Segmentation and Localization in CT Angiography for Coronary Heart Disease Diagnosis by Bo Zhao, Jianjun Peng, Ce Chen, Yongyan Fan, Kai Zhang, Yang Zhang

“…The proposed model incorporates dual-stream processing with channel and spatial attention mechanisms to improve feature extraction. The automatic region-based coronary artery disease diagnostics using the x-ray angiography images (ARCADE) dataset was utilized for model training and evaluation. …”
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Malignant epithelial cell marker–driven risk signature enables precise stratification in esophageal cancer by Hao Zhang, Hao Zhang, Shizhao Cheng, Shizhao Cheng, Yijun Xu, Yijun Xu

“…The model’s predictive value for immune landscape, mutational features, and drug sensitivity was also evaluated. …”
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EmoNet: Deep Attentional Recurrent CNN for X (Formerly Twitter) Emotion Classification by Md. Shakil Hossain, Md. Mithun Hossain, Md. Shakhawat Hossain, M. F. Mridha, Mejdl Safran, Sultan Alfarhood

“…To overcome these challenges, we propose EmoNet, a novel Deep Attentional Recurrent Convolutional Neural Network (DAR-CNN) that integrates an advanced attention mechanism to capture intricate contextual dependencies in textual data. …”
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Improved Connected-Mode Discontinuous Reception (C-DRX) Power Saving and Delay Reduction Using Ensemble-Based Traffic Prediction by Ji-Hee Yu, Yoon-Ju Choi, Seung-Hwan Seo, Seong-Gyun Choi, Hye-Yoon Jeong, Ja-Eun Kim, Myung-Sun Baek, Young-Hwan You, Hyoung-Kyu Song

“…RF extracts traffic features, while TCN captures temporal dependencies in traffic data. …”
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Flood susceptibility mapping using supervised machine learning models: insights into predictors’ significance and models’ performance by Zahid Ur Rahman, Meimei Zhang, Fang Chen, Safi Ullah, Mansoor Ahmad, Aamir Feroz, Samir Shehu Danhassan, Abdullah Azzam

“…Eastern Hindu Kush (EHK) is one of the most flood-prone regions due to its diverse topographic features, complex climatic conditions, and fragile socioeconomic situations. …”
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Machine learning-based process quality control of screen-printed titanium dioxide electrodes by Anesu Nyabadza, Lola Azoulay-Younes, Mercedes Vazquez, Dermot Brabazon

“…Multivariate data analysis techniques such as factor analysis were employed to evaluate the effectiveness of the features extracted from these images. …”
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Validation of Deep Learning–Based Automatic Retinal Layer Segmentation Algorithms for Age-Related Macular Degeneration with 2 Spectral-Domain OCT Devices by Souvick Mukherjee, PhD, Tharindu De Silva, PhD, Cameron Duic, BS, Gopal Jayakar, BS, Tiarnan D.L. Keenan, BM BCh, PhD, Alisa T. Thavikulwat, MD, Emily Chew, MD, Catherine Cukras, MD, PhD

“…Conclusions: In the pursuit of task-specific goals such as retinal layer segmentation, a segmentation network has the capacity to acquire domain-independent features from a large training dataset. …”
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Lung-AttNet: An Attention Mechanism-Based CNN Architecture for Lung Cancer Detection With Federated Learning by Chamak Saha, Somak Saha, Md. Asadur Rahman, Md. Mahmudul Haque Milu, Hiroki Higa, Mohd Abdur Rashid, Nasim Ahmed

“…The convolutional block extracts both low- and high-dimensional features, while LGAM captures feature dependencies across channel and spatial dimensions. …”
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A Concise Dataset for Intelligent Behaviors in Domestic Tasks by Marlon de Oliveira Vaz, Ronnier Frates Rohrich, Joao Alberto Fabro, Andre Schneider de Oliveira

“…The use of high-level intelligent behaviors is critical for overcoming domestic challenges, and ODUTF facilitates the deployment of more reliable deep neural network methods for tracking objects during pick-up tasks. …”
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CDWMamba: Cloud Detection with Wavelet-Enhanced Mamba for Optical Satellite Imagery by Shiyao Meng, Wei Gong, Siwei Li, Ge Song, Jie Yang, Yu Ding

“…In this paper, we propose CDWMamba, a novel dual-domain neural network that integrates the Mamba-based state space model with discrete wavelet transform (DWT) for effective cloud detection. …”
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Enhancing runoff simulation by combining superflex with deep learning methods in China's Qinghai Lake Basin, Northeast Tibetan Plateau by Kaixun Liu, Na Li, Sihai Liang

“…Our approach leverages Superflex as a pre-training step for the neural networks and incorporates key process variables from the physical model as inputs to the network, creating a physically-driven deep learning framework. …”
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DeepGuard: real-time threat recognition using Golden Jackal optimization with deep learning model by Fatma S. Alrayes, Hamed Alqahtani, Wahida Mansouri, Asma Alshuhail, Wafa Sulaiman Almukadi, Ahmed Mahmud

“…The DeepGuard model uses long short-term memory neural networks (LSTM-NNs) for violence detection. The performance evaluation of the DeepGuard model takes place using benchmark datasets. …”
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Hybrid deep learning framework for real-time DO prediction in aquaculture by Longqin Xu, Wenjun Liu, Cai Chengqing, Tonglai Liu, Xuekai Gao, Ferdous Sohel, Murtaza Hasan, Mansour Ghorbanpour, Shahbaz Gul Hassan, Shuangyin Liu

“…This study proposes a water quality estimation model by combining a convolutional neural network (CNN), self-attention (SA), and bidirectional simple recurrent unit (BiSRU). …”
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Short-term solar irradiance forecasting using deep learning models by Syed Saad Ahmed, Chang Wei Bin, Nisar Humaira, Riaz Hannan Naseem, Yeap Kim Ho, Zaber Nursaida Mohamad

“…Furthermore, it is also evaluated whether the model can forecast the amount of Global Horizontal Irradiance (GHI) within one hour given the current recorded features including air temperature, azimuth, cloud opacity, and zenith. …”
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Underwater object detection algorithm integrating image enhancement and deformable convolution by Lijia Guo, Xiangchun Liu, Dongsheng Ye, Xuebao He, Jianxin Xia, Wei Song

“…Second, the backbone network is redesigned via Deformable Convolution v4 (DCNv4), with targeted optimizations applied to enhance the model's capacity for detecting irregularly shaped objects and small-scale targets. …”
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Deep learning classification integrating embryo images with associated clinical information from ART cycles by Mohamed Salih, Christopher Austin, Krishna Mantravadi, Eva Seow, Sutthipat Jitanantawittaya, Sandeep Reddy, Beverley Vollenhoven, Hamid Rezatofighi, Fabrizzio Horta

“…All three models were evaluated against their ability to predict clinical pregnancy and live birth. …”
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Multi-omics analysis reveals the interplay between pulmonary microbiome and host in immunocompromised patients with sepsis-induced acute lung injury by Fan Lu, Ting Huang, Ruichang Chen, Haiyan Yin

“…Bronchoalveolar lavage fluid (BALF) was analyzed using metagenomic next-generation sequencing (mNGS) to assess the pulmonary microbiome, and transcriptomic sequencing evaluated host gene expression. The pulmonary microbiota network in the ICH group showed notable alterations. …”
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