Multidimensional Population Health Modeling: A Data-Driven Multivariate Statistical Learning Approach by Zhiyuan Wei, Adil Baran Narin, Sayanti Mukherjee

“…In this paper, we propose a data-driven multivariate statistical learning approach to simultaneously model various aspects of population health—characterizing the length and quality of life—as a function of health behaviors, clinical care, socioeconomic factors, physical environment, and demographics. …”
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Research on Optimized Algorithm for Deep Learning Based Recognition of Sediment Particles in Turbulent Flow by WANG Hao, YANG Feiqi, ZHANG Lei, WU Wei, XIE Haonan, ZHAO Lin

“…The YOLOv5 algorithm adopted in this study excels at detecting small targets and provides multi-scale detection, strong versatility, fast training, inference speeds, and adaptable fine-tuning capabilities. The YOLOv5 deep learning network structure is enhanced by improving convolutional blocks, incorporating attention mechanisms, and optimizing loss function processing, boosting the detector's overall performance in accurately capturing the motion of particles over short distances. …”
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Defect detection in photolithographic patterns using deep learning models trained on synthetic data by Prashant P. Shinde, Priyadarshini P. Pai, Shashishekar P. Adiga, K. Subramanya Mayya, Yongbeom Seo, Myungsoo Hwang, Heeyoung Go, Changmin Park

“…We then employ state-of-the-art object detection models to investigate defect detection performance as a function of defect size, much smaller than the pitch width. …”
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Efficient and Effective NDVI Time-Series Reconstruction by Combining Deep Learning and Tensor Completion by Ang Li, Menghui Jiang, Dong Chu, Xiaobin Guan, Jie Li, Huanfeng Shen

“…In this article, we novelly combine deep learning with a high-precision spatiotemporal adaptive tensor completion (ST-Tensor) method and propose an end-to-end NDVI time-series reconstruction network (NIT-Net). …”
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Active RIS-NOMA Uplink in URLLC, Jamming Mitigation via Surrogate and Deep Learning by Ghazal Asemian, Mohammadreza Amini, Burak Kantarci

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Multi-model deep learning approach for the classification of kidney diseases using medical images by Waleed Obaid, Abir Hussain, Tamer Rabie, Dhafar Hamed Abd, Wathiq Mansoor

“…Chronic kidney disease is marked by a gradual failure in kidney function due to various factors, such as stones, cysts, and tumors. …”
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Machine learning-based identification of exosome-related biomarkers and drugs prediction in nasopharyngeal carcinoma by Zhengyu Wei, Guoli Wang, Yanghao Hu, Chongchang Zhou, Yuna Zhang, Yi Shen, Yaowen Wang

“…These identified genes underwent functional annotation and pathway enrichment evaluation. …”
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On the Nearshore Significant Wave Height Inversion from Video Images Based on Deep Learning by Chao Xu, Rui Li, Wei Hu, Peng Ren, Yanchen Song, Haoqiang Tian, Zhiyong Wang, Weizhen Xu, Yuning Liu

“…The accuracy of deep learning models in classifying wind wave and swell wave images was investigated, providing reliable classification results for SWH inversion research. …”
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Identification of bacterial key genera associated with breast cancer using machine learning techniques by Md. Kaderi Kibria, Isteaq Kabir Sifat, Md. Bayazid Hossen, Farhana Hasan, Md Parvez Mosharaf, Md Ziaul Hassan

“…Emerging evidence suggests that the gut microbiota, which influences immune function, metabolism, and inflammation, may also play a critical role in BC risk. …”
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Joint Adaptive OFDM and Reinforcement Learning Design for Autonomous Vehicles: Leveraging Age of Updates by Mamady Delamou, Ahmed Naeem, Huseyin Arslan, El Mehdi Amhoud

“…In addition, we exploit adaptive OFDM techniques for dynamic modulation, and we suggest a reward function that leverages the age of updates to handle the communication buffer and improve sensing. …”
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PyCSBtool: Python-Based GUI Learning Tool for Basics Control System Education by C. H. Manathunga, R. A. D. D. Dharmasiri, W. K. Indika L. Wanniarachchi, M. K. Jayananda, Tadachika Nakayama

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Detection of mite infested saffron plants using aerial imaging and machine learning classifier by Hossein Sahabi, Jalal Baradaran-Motie

“…In order to detect affected plants, two support vector machine (SVM) classifiers with radial basis function (RBF) kernels were used separately for NIR and RGB images. …”
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Monitoring and deformation of deep excavation engineering based on DFOS technology and hybrid deep learning by Yanli Peng, Jie Zhao, Yijiang Fan, Cheng Fan

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Robust computation of subcortical functional connectivity guided by quantitative susceptibility mapping: An application in Parkinson’s disease diagnosis by Jianmei Qin, Haoting Wu, Chenqing Wu, Tao Guo, Cheng Zhou, Xiaojie Duanmu, Sijia Tan, Jiaqi Wen, Qianshi Zheng, Weijin Yuan, Zihao Zhu, Jingwen Chen, Jingjing Wu, Chenyu He, Yiran Ma, Chunlei Liu, Xiaojun Xu, Xiaojun Guan, Minming Zhang

“…Previous resting state functional MRI (rs-fMRI) analyses of the basal ganglia in Parkinson’s disease heavily relied on T1-weighted imaging (T1WI) atlases. …”
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Identification of critical biomarkers and immune infiltration in preeclampsia through bioinformatics and machine learning methods by Weiwen Li, Lijun Zhong, Kewen Zhao, Jincheng Xie, Shaodong Deng, Yunyong Fang

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DeepAT: A Deep Learning Wheat Phenotype Prediction Model Based on Genotype Data by Jiale Li, Zikang He, Guomin Zhou, Shen Yan, Jianhua Zhang

“…This provides a data-driven selection criterion for genomic selection, making the selection process more efficient and targeted. Deep learning has become an important tool for phenotype prediction due to its abilities in automatic feature learning, nonlinear modeling, and high-dimensional data processing. …”
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Structure-guided deep learning for back acupoint localization via bone-measuring constraints by Yulong Wang, Tian Lan, Wenjian Dou, Zhi Chen, Song Zhang, Gong Chen, Gong Chen

“…This study introduces a novel automated framework for recognizing back acupoints, uniquely integrating the traditional TCM bone-measuring principle with advanced deep learning for medical image analysis. The method employs an HRFormer backbone network combined with a Structure-Guided Keypoint Estimation Module (SG-KEM) and a structure-constrained loss function, ensuring anatomically consistent predictions within a standardized spatial coordinate system to improve accuracy across diverse body types. …”
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Physical unclonable in-memory computing for simultaneous protecting private data and deep learning models by Wenshuo Yue, Kai Wu, Zhiyuan Li, Juchen Zhou, Zeyu Wang, Teng Zhang, Yuxiang Yang, Lintao Ye, Yongqin Wu, Weihai Bu, Shaozhi Wang, Xiaodong He, Xiaobing Yan, Yaoyu Tao, Bonan Yan, Ru Huang, Yuchao Yang

“…It potentially serves as the hardware infrastructure for edge devices in federated learning or other systems.…”
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Class and Data-Incremental Learning Framework for Baggage Threat Segmentation via Knowledge Distillation by Ammara Nasim, Saad Mazhar Khan, Anum Abdul Salam, Arslan Shaukat, Taimur Hassan, Adeel M. Syed, Muhammad Usman Akram

“…To address these limitations, we propose an incremental learning framework that enables the model to progressively learn new threat categories while retaining previously acquired knowledge. …”
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AI-driven feedback system: Implementing advanced NLP and openAI for online learning by Liberius Sabinus Koe, Cecep Kustandi, Eveline Siregar

“…The research focuses on ensuring that the product can function according to the technical design and fulfil the initial user needs. …”
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