Role of Artificial Intelligence and Personalized Medicine in Enhancing HIV Management and Treatment Outcomes by Ashok Kumar Sah, Rabab H. Elshaikh, Manar G. Shalabi, Anass M. Abbas, Pranav Kumar Prabhakar, Asaad M. A. Babker, Ranjay Kumar Choudhary, Vikash Gaur, Ajab Singh Choudhary, Shagun Agarwal

“…Additionally, AI-powered diagnostic tools, including deep learning imaging and natural language processing, improve screening accuracy, particularly in resource-limited settings. …”
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Automatic Detection for Mining Subsidence Areas Using the CBAM-Enhanced VGG-UNet Model With Long Time Series InSAR Interferograms by Kegui Jiang, Keming Yang, Mengting Gao, Liuguo Zhu, Chuang Jiang

“…The rapid advancements in remote sensing technology and deep learning algorithms have enabled significant breakthroughs in monitoring and accurately identifying mining subsidence. …”
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Research on Concrete Crack and Depression Detection Method Based on Multi-Level Defect Fusion Segmentation Network by Zhaochen Yao, Yanjuan Li, Hao Fu, Jun Tian, Yang Zhou, Chee-Loong Chin, Chau-Khun Ma

“…Cracks and dents in concrete structures are core defects that threaten building safety, but the existing YOLO series algorithms face a huge bottleneck in complex engineering scenarios. …”
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Revolutionizing Diabetes Management Through Nanotechnology-Driven Smart Systems by Aayush Kaushal, Aanchal Musafir, Gourav Sharma, Shital Rani, Rajat Kumar Singh, Akhilesh Kumar, Sanjay Kumar Bhadada, Ravi Pratap Barnwal, Gurpal Singh

“…Nanotechnology offers a groundbreaking approach to diabetes management by leveraging materials at the nanoscale to improve drug delivery, glucose monitoring, and therapeutic precision. …”
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MEP-YOLOv5s: Small-Target Detection Model for Unmanned Aerial Vehicle-Captured Images by Shengbang Zhou, Song Zhang, Chuanqi Li, Shutian Liu, Dong Chen

“…Due to complex backgrounds, significant scale variations of targets, and dense distributions of small objects in Unmanned Aerial Vehicle (UAV) aerial images, traditional object detection algorithms face challenges in adapting to such scenarios. …”
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Addition of Social Determinants of Health to Coronary Heart Disease Risk Prediction: The Multi‐Ethnic Study of Atherosclerosis by Brittany Saldivar Murphy, Yunbi Nam, Robyn L. McClelland, Isaac Acquah, Miguel Cainzos‐Achirica, Khurram Nasir, Wendy S. Post, Melinda C. Aldrich, Andrew P. DeFilippis

“…Incorporation of SDoH into the MESA Risk Score did not improve predictive ability of the model. Our findings do not support the incorporation of SDoH into current risk prediction algorithms.…”
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Blockchain Technology in Supply Chain Management Prospects and Challenges for Implementation by Peshattiwar Atish, P Mohanraj, A Anand Gerald, S Dharmalingam, Tiwari Mohit, G Swarnalakshmi

“…This research proves that the proposed blockchain framework helps to increase the supply chain security level, decrease operational costs, improve transaction efficiency, and conformity with the regulations of global trade through the case study analysis and simulation testing approaches. …”
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Optimizing Stroke Risk Prediction: A Primary Dataset‐Driven Ensemble Classifier With Explainable Artificial Intelligence by Md. Maruf Hossain, Md. Mahfuz Ahmed, Md. Rakibul Hasan Rakib, Mohammad Osama Zia, Rakib Hasan, Md. Rakibul Islam, Md. Shohidul Islam, Md Shahariar Alam, Md. Khairul Islam

“…Future work will focus on incorporating deep learning techniques and medical imaging to further improve classification accuracy and model performance.…”
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Federated Deep Learning for Scalable and Privacy-Preserving Distributed Denial-of-Service Attack Detection in Internet of Things Networks by Abdulrahman A. Alshdadi, Abdulwahab Ali Almazroi, Nasir Ayub, Miltiadis D. Lytras, Eesa Alsolami, Faisal S. Alsubaei, Riad Alharbey

“…ResNet improves feature extraction, VGGNet optimises feature refining, and Swin-Transformer captures contextual dependencies, making the model sensitive to complicated attack patterns across varied network circumstances. …”
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Towards representation learning of radar altimeter waveforms for sea ice surface classification by L. Happ, L. Happ, S. Patil, S. Hendricks, R. Fellegara, L. Kaleschke, A. Gerndt, A. Gerndt

“…We aim to develop new methods for a novel multi-category sea ice and ocean surface classification directly from satellite radar altimeter data to improve sea ice climate data records. Traditional waveform representations are limited to a small set of parameters, leading to information loss. …”
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Comparative analysis of hybrid-SNP microarray and nanopore sequencing for detection of large-sized copy number variants in the human genome by Catarina Silva, José Ferrão, Bárbara Marques, Sónia Pedro, Hildeberto Correia, Ana Valente, António Sebastião Rodrigues, Luís Vieira

“…However, further improvements in variant calling algorithms are still needed for nanopore sequencing to become a highly robust and standardized approach for a comprehensive analysis of genomic structural variation.…”
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Integrating LoRaWAN sensor network and machine learning models to classify beef cattle behavior on arid rangelands of the southwestern United State by Andres Perea, Sajidur Rahman, Huiying Chen, Andrew Cox, Shelemia Nyamuryekung’e, Mehmet Bakir, Huping Cao, Richard Estell, Brandon Bestelmeyer, Andres F. Cibils, Santiago A. Utsumi

“…Monitoring cattle on large, often rugged, rangelands is a daunting task that can be improved using Long Range Wide Area Network (LoRaWAN) tracking and monitoring technology. …”
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Observational study of characteristics and clinical outcomes of Dutch patients with tuberous sclerosis complex and renal angiomyolipoma treated with everolimus. by Bernard A Zonnenberg, Maureen P Neary, Mei Sheng Duh, Raluca Ionescu-Ittu, Jonathan Fortier, Francis Vekeman

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Applications of artificial intelligence and computational intelligence in hydraulic optimization of centrifugal pumps: a comprehensive review by Yuanhui Xu, Xingcheng Gan, Ji Pei, Wenjie Wang, Jia Chen, Shouqi Yuan

“…The findings reveal that the integration of advanced intelligent methods with Computational Fluid Dynamics (CFD) has been widely demonstrated to improve the accuracy, effectiveness, and adaptability of centrifugal pump optimisation. …”
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Development and Validation of a Questionnaire for the Assessment of Diabetic Peripheral Neuropathy: Implications for Clinical Practice in Physical Therapy and Patient Management by Constantin CIUCUREL, Mariana TUDOR, Elena Ioana ICONARU

“…Conclusions: The development and validation of the QAIDPN enhance clinical research and practice by providing a reliable method for evaluating DPN and serving as a foundation for creating targeted physical therapy algorithms aimed at improving patient outcomes.…”
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Predicting adolescent psychopathology from early life factors: A machine learning tutorial by Faizaan Siddique, Brian K. Lee

“…The best performing algorithms were elastic net and gradient boosted trees. …”
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Timeseries Fault Classification in Power Transmission Lines by Non-Intrusive Feature Extraction and Selection Using Supervised Machine Learning by Rab Nawaz, Hani A. Albalawi, Syed Basit Ali Bukhari, Khawaja Khalid Mehmood, Muhammad Sajid

“…Feature selection through dimensionality reduction techniques is used to improve model performance and more efficient use of computational resources. …”
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Cervical cancer demystified: exploring epidemiology, risk factors, screening, treatment modalities, preventive measures, and the role of artificial intelligence by N. Mohammad, M. Khan, M. Maqsood, A. H. K. Naseeb

“…These innovations have the potential to enhance diagnostic accuracy, reduce human error, and improve patient outcomes, particularly in resource-limited settings. …”
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FQDNet: A Fusion-Enhanced Quad-Head Network for RGB-Infrared Object Detection by Fangzhou Meng, Aoping Hong, Hongying Tang, Guanjun Tong

“…This mechanism significantly improves detection performance, particularly for small objects. …”
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Diagnosis of Lung Cancer Using Endobronchial Ultrasonography Image Based on Multi-Scale Image and Multi-Feature Fusion Framework by Huitao Wang, Takahiro Nakajima, Kohei Shikano, Yukihiro Nomura, Toshiya Nakaguchi

“…The primary aim of this study is to develop a computer-aided diagnosis (CAD) system for lung cancer using endobronchial ultrasonography (EBUS) images and deep learning algorithms to facilitate early detection and improve patient survival rates. …”
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