Deep Learning Applications in Ionospheric Modeling: Progress, Challenges, and Opportunities by Renzhong Zhang, Haorui Li, Yunxiao Shen, Jiayi Yang, Wang Li, Dongsheng Zhao, Andong Hu

“…Additionally, this study explores the potential of deep learning in ionospheric modeling for the early warning of geological hazards such as earthquakes, volcanic eruptions, and tsunamis, offering new insights for constructing ionospheric-geological activity warning models. Looking ahead, research will focus on developing hybrid models that integrate physical modeling with deep learning, exploring adaptive learning algorithms and multi-modal data fusion techniques to enhance long-term predictive capabilities, particularly in addressing the impact of climate change on the ionosphere. …”
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Sweet Potato Yield Prediction Using Machine Learning Based on Multispectral Images Acquired from a Small Unmanned Aerial Vehicle by Kriti Singh, Yanbo Huang, Wyatt Young, Lorin Harvey, Mark Hall, Xin Zhang, Edgar Lobaton, Johnie Jenkins, Mark Shankle

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Automotive navigation for mobile robots: Comprehensive review by Mayar Abdullah Taleb, Gyula Korsoveczki, Géza Husi

“…This research intends to bridge the gap between theoretical algorithms and their implementation in real-world scenarios through theoretical analysis, comparative evaluation, and practical field tests. …”
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Novel Approaches for the Early Detection of Glaucoma Using Artificial Intelligence by Marco Zeppieri, Lorenzo Gardini, Carola Culiersi, Luigi Fontana, Mutali Musa, Fabiana D’Esposito, Pier Luigi Surico, Caterina Gagliano, Francesco Saverio Sorrentino

“…The inclusion criteria were limited to research published in English in peer-reviewed publications that used AI, ML, or DL to diagnose or treat glaucoma in human subjects. …”
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Leveraging dendritic complexity for neuromorphic computing by Suma G Cardwell, Mark Plagge, Luke Parker, Claire E Plunkett, David Munkvold, Paloma T Gonzalez-Bellido, Scott Koziol, Conrad James, Frances S Chance

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Quantum Technologies for Beyond 5G and 6G Networks: Applications, Opportunities, and Challenges by Engin Zeydan, Chamitha De Alwis, Rabia Khan, Yekta Turk, Abdullah Aydeger, Thippa Reddy Gadekallu, Madhusanka Liyanage

“…Finally, we summarize the lessons learned from current research and outline future research directions to guide the ongoing development of quantum-enabled 6G networks.…”
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Identifying potential biomarkers and molecular mechanisms related to arachidonic acid metabolism in vitiligo by Xiaoqing Li, Xiaoqing Li, Li Yang, Longfei Zhu, Jingying Sun, Jingying Sun, Cuixiang Xu, Cuixiang Xu, Lijun Sun, Lijun Sun

“…These findings offer insights into vitiligo treatment, although further research is needed for a comprehensive understanding.…”
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A novel ensemble model for multi-temporal forest vegetation classification: integrating spectral-temporal features and topographic constraints by Rongfei Duan, Chunlin Huang, Peng Dou, Jinliang Hou, Ying Zhang

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Determining time since deposition of latent fingerprints on forensic adhesive tape using ultrafast DESI-MS and machine learning by Nora Rajs, Yinon Harush-Brosh, Ron Raisch, Ravit Yakobi Arancibia, Amani Zoabi, Guy Nevet Golan, Moshe Shpitzen, Sarena Wiesner, Michal Levin-Elad, Tommy Kaplan, Katherine Margulis

“…Data analysis using the XGBoost and SMOTE algorithms achieved a correlation of 0.54 (p-value < 1e−5) between TSD prediction and true TSD, achieving 83.3% accuracy in distinguishing between 0-4 days and 10–15 days old prints. …”
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Crowdsourcing geographic information for terrorism-related disaster awareness and mitigation: perspectives and challenges by Michaelmary Chukwu, Xiao Huang, Siqin Wang, Di Yang, Xinyue Ye

“…Notably, we placed particular emphasis on the integration of Machine Learning (ML) algorithms in studying crowdsourced terrorism geoinformation to assess the current state of research and propose future directions. …”
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Biomedical Data Analysis Systems for the Diagnosis of Skin Neoplasms by O. O. Myakinin

“…Materials and methods. Algorithms of software modules developed for optical systems of our own design are presented. …”
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Data Mining Techniques for Early Detection and Classification of Plant Diseases: An Optimization-Based Approach by Wagh Swapnil, Sharma Ruchi

“…Early diagnosis and efficient categorization of plant diseases are of utmost importance to support agricultural production and profitability. Besides, this research aims to investigate the feasibility that employs data mining framework together with optimization algorithms as approaches towards plant diseases identification and categorization systems. …”
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Supporting self-management with an internet intervention for low back pain in primary care: a RCT (SupportBack 2) by Adam W A Geraghty, Taeko Becque, Lisa C Roberts, Jonathan Hill, Nadine E Foster, Lucy Yardley, Beth Stuart, David A Turner, Gareth Griffiths, Frances Webley, Lorraine Durcan, Alannah Morgan, Stephanie Hughes, Sarah Bathers, Stephanie Butler-Walley, Simon Wathall, Gemma Mansell, Malcolm White, Firoza Davies, Paul Little

“…Costs were estimated using data from general practice patient records. Researchers involved in data collection and statistical analysis were blind to group allocation. …”
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Prognostic and immunological implications of cathepsin Z overexpression in prostate cancer by Junyue Tao, Junyue Tao, Junyue Tao, Yiding Chen, Yiding Chen, Yiding Chen, Xiaokang Bian, Xiaokang Bian, Xiaokang Bian, Tingting Cai, Tingting Cai, Tingting Cai, Changhao Song, Changhao Song, Changhao Song, Chaozhao Liang, Chaozhao Liang, Chaozhao Liang, Zongyao Hao, Zongyao Hao, Zongyao Hao, Jialing Meng, Jialing Meng, Jialing Meng, Qintao Ge, Qintao Ge, Jun Zhou, Jun Zhou, Jun Zhou

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A Modular, Model, Library Framework (DebrisLib) for Non-Newtonian Geophysical Flows by Ian E. Floyd, Alejandro Sánchez, Stanford Gibson, Gaurav Savant

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A Review of Neuro-ML Breakthroughs in Addressing Neurological Disorders by Cosmina-Mihaela Rosca, Adrian Stancu

“…This research aims to explore the interdisciplinary connection between the field of neurology and artificial intelligence (AI) through machine learning (ML) algorithms. …”
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Problems of optimizing the energy consumption of households in the tasks of improving the energy efficiency of the housing sector by G. G. Grebenuk, S. M. Nikishov, A. A. Krygin, L. A. Sereda

“…Thus, the general plan of research in this paper is as follows:• carry out grouping of devices by the way of setting functionalrequirements;• determine the acceptable composition and type of input data forthe user;• define the minimum set of input data for formalizing the limitationof the total power consumption;• design optimization algorithms that work with the input dataspecified above. …”
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Does Artificial Intelligence Bring New Insights in Diagnosing Phlebological Diseases?—A Systematic Review by Sergiu-Ciprian Matei, Sorin Olariu, Ana-Maria Ungureanu, Daniel Malita, Flavia Medana Petrașcu

“…This study aims to evaluate the efficacy and feasibility of AI algorithms in diagnosing venous diseases and explore their potential impact on clinical practice. …”
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A review of recent artificial intelligence for traditional medicine by Chengbin Hou, Yanzhuo Gao, Xinyu Lin, Jinchao Wu, Ning Li, Hairong Lv, William Cheng-Chung Chu

“…Specifically, we investigate how Machine Learning, Deep Learning, and Large Language Models are applied to TM, covering applications such as diagnosis (before, during, after) and research (drug research, structured knowledge, data analysis). …”
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Trends in the sustainable use of artificial intelligence: a bibliometric approach by Alejandro Valencia-Arias, Jesus Alberto Jimenez Garcia, Toño Eldrin Alvites Adan, Ezequiel Martínez Rojas, Jackeline Valencia, Erica Agudelo-Ceballos, Hernán Uribe Bedoya, Gustavo Adolfo Moreno López

“…An interdisciplinary research agenda was proposed to address these topics.…”
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