Machine learning with the body roundness index and associated indicators: a new approach to predicting metabolic syndrome by Yaxuan He, Zekai Chen, Zhaohui Tang, Yuexiang Qin, Fang Wang

“…Ten machine learning algorithms were evaluated using 10-fold cross-validation. …”
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Machine learning to predict virological failure among HIV patients on antiretroviral therapy in the University of Gondar Comprehensive and Specialized Hospital, in Amhara Region, E... by Daniel Niguse Mamo, Tesfahun Melese Yilma, Makda Fekadie Tewelgne, Yakub Sebastian, Tilahun Bizuayehu, Mequannent Sharew Melaku, Agmasie Damtew Walle

“…This study used different machine learning classification algorithms to predict the features that cause virological failure in HIV-positive patients. …”
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The Relationship Between Stiff Knee Gait Runner’s Dystonia and Musculoskeletal Knee Pathology: A Case Series by Jared A. Stowers, Derek S. Day, Steven Jow, Sarah Heins, Euan Forrest, Yonathan M. Assefa, Paige M. Lind, Afreen Mushtaheed, Frances T. Sheehan, Katharine E. Alter

“…Methods: Eight RD cases, evaluated at the NIH Movement Disorders Clinic since 2018, were retrospectively reviewed. …”
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Simple energy detector for two-stage classification for antidrone systems by Zurovac Snežana, Petrović Nikola, Joksimović Vasilija, Pokrajac Ivan, Mikanović Darko, Sazdić-Jotić Boban

“…Furthermore, we conducted a comparative analysis of different deep learning algorithms at the outset of twostage classification, which is a potential basis for adopting this approach.…”
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Assessing marine ecosystem risks through unsupervised methods by Laura Pavirani, Pasquale Bove, Gianpaolo Coro

“…Traditional approaches, such as Ecosystem Models (EMs) and Marine Spatial Planning (MSP), often rely on expert knowledge, which introduces subjective assumptions. This study evaluates six unsupervised methods — four clustering algorithms (Multi K-means, Fuzzy C-means, X-means, and DBSCAN) and two machine-learning models (an Artificial Neural Network, ANN, and a Variational Autoencoder, VAE) — to assess marine ecosystem risk in the Mediterranean Sea automatically, using open-access data from 2017 to 2021. …”
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Are Artificial Intelligence Models Listening Like Cardiologists? Bridging the Gap Between Artificial Intelligence and Clinical Reasoning in Heart-Sound Classification Using Explain... by Sami Alrabie, Ahmed Barnawi

“…Second, we noticed inconsistent accuracy scores across different pretrained models, prompting the need for interpretable explanations to validate these results. …”
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Assessing the effects of therapeutic combinations on SARS-CoV-2 infected patient outcomes: A big data approach. by Hamidreza Moradi, H Timothy Bunnell, Bradley S Price, Maryam Khodaverdi, Michael T Vest, James Z Porterfield, Alfred J Anzalone, Susan L Santangelo, Wesley Kimble, Jeremy Harper, William B Hillegass, Sally L Hodder, National COVID Cohort Collaborative (N3C) Consortium

“…Then, the most accurate model is utilized by eXplainable Artificial Intelligence (XAI) algorithms to provide insights about the learned treatment combination impacts on the model's final outcome prediction.…”
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Higher-order aberrations and spherical aberration in various age groups after LASIK and cataract surgery by Robert Edward T. Ang, Patricia L. Lee, Ryan S. Torres, Michelle Marie Q. Araneta, Emerson M. Cruz, Maria Socorro M. Torno

“…Treated patients were classified into 2 groups according to treatment administered: eyes that underwent different algorithms of laser in situ keratomileusis (Lasik) demonstrating quantifiable differences in corneal aberrations, and eyes that underwent uncomplicated phacoemulsification with in-the-bag implantation of aspheric neutral EnVista MX60 (Bausch & Lomb, USA), negative aspheric Tecnis ZCB00 (Johnson and Johnson, USA), or spherical Akreos Adapt (Bausch & Lomb, USA) intraocular lens (IOL) showing differences in internal spherical aberrations. …”
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Exploring the key ingredients and mechanisms of Banxia Xiexin decoction for the treatment of polycystic ovary syndrome based on network pharmacology and experimental validation by Bai Hai, Yingying Zhang, Jing Huang, Richard Mprah, Mingming Wang

“…KEGG analysis showed they were mainly involved in signaling pathways such as PI3K-AKT, MAPK, HIF-1 and IL17. By PPI and algorithmic analysis, we identified 8 hub genes, 5 of which (JUN, MAPK1, MAPK3, FOS, TP53) were related to oxidative stress. …”
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Nonlinear oscillations of a lumped system with series spring, piezoelectric device, and feedback controller by M. K. Abohamer, T. S. Amer, A. A. Galal, Mona A. Darweesh, A. Arab, Taher A. Bahnasy

“…Additionally, resonance frequency curves are plotted to assess stability/instability and evaluate the solutions at steady-state.…”
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DREFNet: Deep Residual Enhanced Feature GAN for VVC Compressed Video Quality Improvement by Tanni Das, Kiho Choi

“…While the advanced algorithms used by these modern codecs can effectively decrease file sizes and enhance compression efficiency, they frequently find it challenging to eliminate artifacts entirely. …”
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Multi-crop plant counting and geolocation using a YOLO-Powered GUI System by Renato Herrig Furlanetto, Nathan Schawn Boyd, Ana Claudia Buzanini

“…Crop counting has traditionally relied on manual field assessments or complex machine learning algorithms, which often struggle to identify small objects or underestimate the total count of objects present in the field. …”
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Visual impairment prevention by early detection of diabetic retinopathy based on stacked auto-encoder by Shagufta Almas, Fazli Wahid, Sikandar Ali, Ahmed Alkhyyat, Kamran Ullah, Jawad Khan, Youngmoon Lee

“…Experimental results across different training/testing ratios (50:50, 60:40, 70:30, and 75:25) showcase the model’s robustness. …”
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Controlling user access with scripting to mitigate cyber-attacks by Owusu Nyarko-Boateng, Isaac Kofi Nti, Anastasia Akyamaa Mensah, Emmanuel Kojo Gyamfi

“…The adopted script metrics deployed such as Script Execution Time, Resources Utilization, Success Rate and Error Rate helped in evaluating the performance, efficiency, and effectiveness of the scripts. …”
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Analysis of the molecular subtypes and prognostic models of anoikis-related genes in colorectal cancer by Lei Shen, Kang Hou, Jifeng Zhang, Xiaodong Li

“…Additionally, various computational algorithms were employed to evaluate the immunotherapeutic responses of different risk groups. …”
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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

“…Compared to state-of-the-art RGB-IR object detection algorithms, our method strikes a better balance between detection accuracy and computational efficiency while exhibiting strong robustness across diverse detection scenarios.…”
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Sensor‐Guided Smart Irrigation for Tomato Production: Comparing Low and Optimum Soil Moisture in Greenhouse Environments by Ibrahim Dirlik, Ferhat Uğurlar, Cengiz Kaya

“…ABSTRACT Effective irrigation management is crucial for optimizing crop production, particularly in water‐scarce regions. This study evaluated the performance of an Arduino‐based system designed to monitor and control soil moisture in a greenhouse setting, focusing on its impact on tomato plant growth, fruit yield, and fruit size under two different irrigation treatments. …”
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Duck Egg Crack Detection Using an Adaptive CNN Ensemble with Multi-Light Channels and Image Processing by Vasutorn Chaowalittawin, Woranidtha Krungseanmuang, Posathip Sathaporn, Boonchana Purahong

“…The Adaptive MobileNetV2 was employed to evaluate the performance of crack detection under different lighting and pre-processing conditions. …”
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Intracranial atherosclerosis: structure, clinical aspects and risk factors by Marine M. Tanashyan, Andrey S. Mazur, Anton A. Raskurazhev, Anna N. Berliand, Marina V. Dreval, Polina I. Kuznetsova, Оlga V. Lagoda

“…Active research is underway to determine the prevalence of intracranial atherosclerosis across different ethnic groups, the role of modifiable and non-modifiable risk factors in its pathogenesis, and the advances in diagnostic algorithms for patients with extra-/intracranial atherosclerosis. …”
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EPIGENETIC REGULATION OF GENE EXPRESSION IN HEAD AND NECK SQUAMOUS CELL CARCINOMA: THERAPEUTIC PERSPECTIVES by R. B. Samsonov, Z. A. Radzhabova, Yu. V. Cheburkin, V. A. Klyuge, E. V. Tkachenko, A. V. Malek

“…Along with the importance of investigation of typical for HNT genetic abnormalities, we should also stress studying of epigenetic regulation disorders in tumor cells because of its particular practical value.This review is aimed to analyze the relationship between different mechanisms of epigenetic regulation of gene expression, and to evaluate this relationship in squamous cell HNT.  …”
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