Weighted Hybrid Random Forest Model for Significant Feature prediction in Alzheimer’s Disease Stages by M. Rohini, D. Surendran

“…Abstract In recent studies, several machine learning and deep learning prediction models have been proposed for the early detection and classification of various stages of Alzheimer’s Disease (AD). …”
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Deep learning-based analysis of daily activity patterns of farmed dromedary camels by Rama Al-Khateeb, Nabil Mansour, Nabil Mansour, Shaher Bano Mirza, Fouad Lamghari

“…In Phase 2, the study expanded to include six camels, enabling an evaluation of individual behavioral variations. The YOLOv7 object detection algorithm was used to train and validate the model on images extracted from the recordings, achieving high accuracy in detecting and classifying the defined activities.ResultsThe results showed notable variations in activity patterns between Phases 1 and 2. …”
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Breast Tumor-Like-Masses Segmentation From Scattering Images Obtained With an Ultrahigh-Sensitivity Talbot-Lau Interferometer Using Convolutional Neural Networks by Ionut-Cristian Ciobanu, Nicoleta Safca, Elena Anghel, Dan Popescu

“…Segmentation of breast tumors using imaging techniques remains a critical challenge in medical diagnostics, with limitations in contrast and resolution affecting early detection. Conventional mammography methods still have some limitations in differentiating between healthy and tumorous tissue, particularly in cases with low-density differences. …”
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Aerial image segmentation of embankment dams based on multispectral remote sensing: a case study in the Belo Monte Hydroelectric Complex, Pará, Brazil by Carlos André de Mattos Teixeira, Thabatta Moreira Alves de Araujo, Evelin Cardoso, Marcos Antonio Costantin Filho, João Weyl Costa, Carlos Renato Lisboa Frances

“…The main objectives of this study are to assess the classification performance of the algorithm in segmenting earth-rock dams and the contribution of non-visible band reflectance data to the overall model performance. …”
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Assessment of Cognitive Function with Sleep Spindle Characteristics in Adults with Epilepsy by Yajin Huang, Yaqing Liu, Wenjun Song, Yanjun Liu, Xiaoqian Wang, Juping Han, Jiang Ye, Hongmei Han, Li Wang, Juan Li, Tiancheng Wang

“…Spindle characteristics during N2 sleep were extracted using a learning-based system for sleep staging and an automated spindle detection algorithm. We investigated the difference between cognitive subgroups in spindle characteristics. …”
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Body mass index as the main predictor for length of stay in COVID-19 patients with mild and moderate symptoms: a cross-sectional study in COVID-19 emergency hospital in Indonesia by Siti Rahayu Nadhiroh, Anisa Lailatul Fitria, Armedy Ronny Hasugian, Erwin Astha Triyono, Nono Tri Nugroho, Alfadhila Khairil Sinatrya, Hazreen B Abdul Majid

“…The Chi-square automatic interaction detection (CHAID) algorithm was employed for model building. …”
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RivAIr: A custom-designed UAV-based sensor for real-time water area segmentation and surface velocity estimation by Marco La Salandra, Rosa Colacicco, Simone Panza, Giovanni Fumai, Pierfrancesco Dellino, Domenico Capolongo

“…This self-contained, edge-computing module integrates custom hardware with real-time machine learning and optical flow algorithms, enabling onboard water segmentation and river surface velocity estimation. …”
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ICD-10-AM codes for cirrhosis and related complications: key performance considerations for population and healthcare studies by Kelly L Hayward, Amy L Johnson, Benjamin J Mckillen, Vikas Bansal, Leigh U Horsfall, Gunter Hartel, Chris Moser, Elizabeth E Powell, Patricia C Valery

“…Overall accuracy was lower for spontaneous bacterial peritonitis (‘grouped’ PPV 0.75; κ 0.73) and the poorest for encephalopathy (‘grouped’ PPV 0.55; κ 0.21). To optimise detection of cirrhosis-related encounters, an ICD-10-AM code algorithm was constructed and validated in an independent cohort of 116 patients with known cirrhosis.Conclusion Multiple ICD-10-AM codes should be considered when using administrative databases to study the burden of cirrhosis and its complications in Australia, to avoid underestimation of the prevalence, morbidity, mortality and related resource utilisation from this burgeoning chronic disease.…”
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The Impact of Atmospheric Rivers on Precipitation and Their Contribution to Crustal Deformation in Greenland, 2010 to 2019 by Wenhao Li, Xinyu Qin, Tingting Zhu, Jintao Lei, C. K. Shum, Fei Li, Shengkai Zhang

“…This article utilizes MERRA-2 reanalysis data and the vIVT algorithm to statistically analyze the frequency, duration, and spatiotemporal distribution of ARs landings in Greenland from 2010 to 2019. …”
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Application of the U-Net Deep Learning Model for Segmenting Single-Photon Emission Computed Tomography Myocardial Perfusion Images by Ahmad Alenezi, Ali Mayya, Mahdi Alajmi, Wegdan Almutairi, Dana Alaradah, Hamad Alhamad

“…Machine learning (ML) algorithms have demonstrated superior performance in addressing segmentation problems. …”
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Complex Cloud-Sea Background Simulation for Space-Based Infrared Payload Digital Twin by Wen Sun, Yejin Li, Fenghong Li, Guangsen Liu, Peng Rao

“…To address challenges like limited data samples and simulate infrared images in various scenarios, this study proposes a hybrid data-driven and fractal-driven cloud-sea scenario simulation approach for high-precision infrared images at space-based detection scales. Static cloud-sea scenes are generated using Qilu-2 and New Technology satellite images, while dynamic scenarios are simulated with our iterative fractal dimension optimization algorithm. …”
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Trusted Energy-Aware Hierarchical Routing (TEAHR) for Wireless Sensor Networks by Vikas, Charu Wahi, Bharat Bhushan Sagar, Manisha Manjul

“…The comparisons of TEAHR with conventional techniques show that the proposed algorithm reduces total latency by 15%, enhances energy efficiency by around 20%, and maintains a stable packet forwarding rate, which is highly desirable for accurate operation in adversarial environments, as demonstrated through comparative analysis. …”
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On-Demand Gait-Synchronous Electrical Cueing in Parkinson's Disease Using Machine Learning and Edge Computing: A Pilot Study by Ardit Dvorani, Constantin Wiesener, Christina Salchow-Hommen, Magdalena Jochner, Lotta Spieker, Matej Skrobot, Hanno Voigt, Andrea Kuhn, Nikolaus Wenger, Thomas Schauer

“…By avoiding this we aim at improving usability, robustness, and detection delay. <italic>Methods:</italic> We present a new technical solution, that runs detection and cueing algorithms directly on the sensing and cueing devices, bypassing the smartphone. …”
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SPATIO-TEMPORAL CLUSTER ANALYSIS OF DISEASE by M. S. Abramovich, S. V. Anishchanka, M. M. Mitskevich, O. I. Bydanov

“…Spatio-temporal cluster analysis algorithms were used for the cluster detection of incidence of thyroid carcinoma. …”
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Advancements in the use of AI in the diagnosis and management of inflammatory bowel disease by Dalia Braverman-Jaiven, Luigi Manfredi

“…To tackle this, more annotated colonoscopy images and videos will be required for the training of new and more reliable AI algorithms. This article discusses the current challenges in the early detection of IBD, focusing on the available AI algorithms, and databases, and the challenges ahead to improve the detection rate.…”
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Digital Image Copyright Protection and Management Approach—Based on Artificial Intelligence and Blockchain Technology by Jikuan Xu, Jiamin Zhang, Junhan Wang

“…It introduces an originality detection model based on deep learning technology after conducting both off-chain and on-chain detection of unidentified images, providing triple protection for digital image copyright infringement detection and enabling efficient active defense and passive evidence storage. …”
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River Surface Space–Time Image Velocimetry Based on Dual-Channel Residual Network by Ling Gao, Zhen Zhang, Lin Chen, Huabao Li

“…However, environmental interference often blurs weak tracer textures in STIs, limiting the accuracy of traditional MOT detection algorithms based on shallow features like images’ gray gradient. …”
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A Systematic Literature Review of Concept Drift Mitigation in Time-Series Applications by Mujaheed Abdullahi, Hitham Alhussian, Norshakirah Aziz, Said Jadid Abdulkadir, Yahia Baashar, Abdussalam Ahmed Alashhab, Afroza Afrin

“…The findings show that Support Vector Machines (SVM) is the most effective learning algorithms for the detection and adaptation of CD in regression and classification tasks using time-series data. …”
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THE PROBLEMS OF PROVIDING INFECTIOUS DISEASE SAFETY FOR ORGAN AND TISSUE DONATION BY SCREENING BLOOD-BORNE VIRAL INFECTIONS by M. Sh. Khubutiya, S. A. Solonin, M. A. Godkov

“…It is shown that the current screening algorithm doesn’t allow detecting hidden forms of BBVIs.…”
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Research on Method for Intelligent Recognition of Deep-Sea Biological Images Based on PSVG-YOLOv8n by Dali Chen, Xianpeng Shi, Jichao Yang, Xiang Gao, Yugang Ren

“…Nonetheless, the inherent complexities of the deep-sea environment, the scarcity of available deep-sea organism samples, and the significant refraction and scattering effects of underwater light collectively impose formidable challenges on the current detection algorithms. To address these issues, we propose an advanced deep-sea biometric identification framework based on an enhanced YOLOv8n architecture, termed PSVG-YOLOv8n. …”
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