Medical image segmentation assisted with clinical inputs via language encoder in a deep learning framework by Hengrui Zhao, Biling Wang, Deepkumar Mistry, Jing Wang, Michael Dohopolski, Daniel Yang, Weiguo Lu, Steve Jiang, Dan Nguyen

“…Methods: We propose a deep learning-based medical image segmentation framework designed to mimic the clinical process of delineating CTVs and OARs. At its core, the model performs precise segmentation of medical images while enhancing accuracy by integrating clinical information in text format. …”
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Development and validation of a novel nomogram to predict worsening of gastroesophageal reflux symptoms after laparoscopic sleeve gastrectomy using Lasso-logistic regression by Lei Jin, Xiao-Kun Huang, Zhen-Yu Gao, Jing Gu, Zhe Zhang, Fei-Qi Xu, Ying Li, Hao-Peng Zhu, Cheng-Fei Du, Jun-Wei Liu, Lei Liang, Zhi-Fei Wang, Xiao-Dong Sun, Zun-Qiang Xiao, Yao-Juan Wu

“…These 5 predictor variables constructed a model with moderate predictive power, with an area under the ROC curve of 0.779 for the training set and 0.796 for the validation set. …”
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Contactless Detection of Abnormal Breathing Using Orthogonal Frequency Division Multiplexing Signals and Deep Learning in Multi-Person Scenarios by Muneeb Ullah, Xiaodong Yang, Zhiya Zhang, Tong Wu, Nan Zhao, Lei Guan, Malik Muhammad Arslan, Akram Alomainy, Hafiza Maryum Ishfaq, Qammer H. Abbasi

“…Future work will expand the dataset and refine the models to improve performance across diverse respiratory patterns and real-world data from a respiratory unit.…”
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Corn Seed Freezing Damage Identification of Different Sides Based on Hyperspectral Imaging and SPA-2DCOS Fusion Algorithm by Jun Zhang, Limin Dai, Ruiyuan Zhuang

“…When the fusion algorithm consisting of SPA and 2D-COS was used, the model’s performance on the endosperm side was better than that of the full-waveband analysis with only 19 feature wavelengths, while the recognition effect on embryo side could be achieved with only 15 feature wavelengths. …”
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Machine Learning Classification Strategy to Improve Streamflow Estimates in Diverse River Basins in the Colorado River Basin by Sarah Maebius, K. E. Bennett, J. Schwenk

“…Lastly, we model streamflow in each category with climate and anthropogenic proxy data sets and use feature importance methods to assess whether model performance improves with additional relevant data. …”
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Defect Detection Method of Carbon Fiber Unidirectional Band Prepreg Based on Enhanced YOLOv8s by Weipeng Su, Mei Sang, Yutong Liu, Xueming Wang

“…The attention mechanisms are inserted between the backbone network and the detection head, respectively, to enhance feature extraction before target localization. The YOLOv8s-GAM model achieves a mean average precision (mAP@0.5) of 84.4%, precision of 79.3%, and recall of 78.3%, while the YOLOv8s-DLKA model shows improved performance with mAP@0.5 of 86.4%, precision of 82.4%, and recall of 80.2%. …”
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Enhancing freight train delay prediction with simulation‐assisted machine learning by Niloofar Minbashi, Jiaxi Zhao, C. Tyler Dick, Markus Bohlin

“…The model's performance on three data sets—a real‐world European yard, a baseline simulation, and an ultimate randomness simulation for a comparable North American yard—shows a respective R2 of 0.90, 0.87, and 0.70. …”
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Early Immunological and Inflammation Proteomic Changes in Elderly COVID-19 Patients Predict Severe Disease Progression by Shiyang Liu, Wen Xu, Bo Tu, Zhiqing Xiao, Xue Li, Lei Huang, Xin Yuan, Juanjuan Zhou, Xinxin Yang, Junlian Yang, De Chang, Weiwei Chen, Fu-Sheng Wang

“…LASSO regression screened features followed by logistic regression and receiver operating characteristic (ROC) analysis to optimize the model by incrementally incorporating features ranked by random forest importance. …”
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An Improved Lithium-Ion Battery Fire and Smoke Detection Method Based on the YOLOv8 Algorithm by Li Deng, Di Kang, Quanyi Liu

“…By integrating advanced modules for richer feature extraction and streamlined architecture, YFSNet significantly enhances detection precision and real-time performance. …”
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Refining breast cancer classification: Customized attention integration approaches with dense and residual networks for enhanced detection by Mohammad Sakif Alam, Anwar Hossain Efat, SM Mahedy Hasan, Md Palash Uddin

“…The attention mechanisms focus on regionally important features, improving classification accuracy. A triple-level ensemble (TLE) method combines the performance of multiple models, further enhancing prediction accuracy. …”
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Evaluating impact of different factors on electric vehicle charging demand by Shakker Soheila, Esmi Nima, Shahbahrami Asadollah

“…Leveraging long short-term memory networks – effective in modeling time-series data – we evaluate the impact of contextual features on forecasting performance. …”
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Automated identification of sedimentary structures in core images using object detection algorithms. by Ammar J Abdlmutalib, Korhan Ayranci, Umair Bin Waheed, Hamad D Alhajri, James A MacEachern, Mohammed N Al-Khabbaz

“…Although Faster R-CNN reached a higher mean average precision (94.44%), it exhibited lower recall, particularly for frequently occurring structures. Both models faced challenges in distinguishing morphologically similar features, such as mud drapes and bioturbated media. …”
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Predicting traffic flow between bike-sharing system stations: A case study of Chicago by Ali Behroozi, Ali Edrisi

“…Furthermore, this research compares two performance models for predicting traffic flow. This research not only aids in optimizing bicycle distribution but also lays the groundwork for predicting demand in other public transportation systems, such as subways and buses, utilizing smart card technology.…”
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NeuroTIS+: An Improved Method for Translation Initiation Site Prediction in Full-Length mRNA Sequence via Primary Structural Information by Wenqiu Xiao, Chao Wei

“…Second, it neglects the heterogeneity of negative TISs originating from different reading frames, which exhibit distinct coding features in their vicinity. In this paper, under the framework of NeuroTIS, we propose its enhanced version, NeuroTIS+, which allows for more sophisticated codon label dependency modeling via temporal convolution and homogenous feature building through an adaptive grouping strategy. …”
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Cancelable Multi-Branch Deep Learning Framework for Privacy-Preserving ECG Biometric Authentication by Mohamed Hammad, Ali Abdullah S. AlQahtani, Mohammed ELAffendi, Abdelhamied A. Ateya, Nebojsa Bacanin

“…This paper presents a novel cancelable ECG biometric authentication framework that integrates a Cancelable Dynamic Biometric Transformation (CDBT) with a multi-branch deep learning architecture to enhance both privacy and performance. The proposed model captures varied ECG feature representations via parallel convolutional branches and transforms them into non-invertible templates using a fixed-key CDBT method. …”
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Exploring Applications of Convolutional Neural Networks in Analyzing Multispectral Satellite Imagery: A Systematic Review by Antonia Ivanda, Ljiljana Šerić, Maja Braović

“…, RQ2: “What are the commonly utilized MSI datasets for training CNN models in the context of processing multispectral satellite imagery?”…”
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The analysis of acquisition system for electronic traffic signal in smart cities based on the internet of things by Yue Ma, Chenglong Wang, Tianlei Fu, Ziting Meng

“…Furthermore, the average detection time of the model is 20.5 milliseconds, indicating good real-time performance. …”
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Eccentric Compression Behavior of Coral Aggregate Geopolymer Concrete Columns Reinforced with Stainless-Steel Rebars by Haiwen Xu, Jiasheng Jiang, Chao Yang

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Attention residual network for medical ultrasound image segmentation by Honghua Liu, Peiqin Zhang, Jiamin Hu, Yini Huang, Shanshan Zuo, Lu Li, Mailan Liu, Chang She

“…For instance, while the U-Net model has demonstrated a favorable performance in medical image segmentation, the convolution layers of the traditional U-Net model are relatively simplistic, leading to suboptimal extraction of global information. …”
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The Application of Lite-GRU Embedding and VAE-Augmented Heterogeneous Graph Attention Network in Friend Link Prediction for LBSNs by Ziteng Yang, Boyu Li, Yong Wang, Aoxue Liu

“…The results show that the GEVEHGAN model outperforms other comparative models in evaluation metrics such as AUC, AP, and Top@K accuracy, demonstrating its superior performance in the friend link prediction task.…”
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