Applications of remote sensing and GIS techniques for identifying of the plastic waste from space: Evidence from Khulna city corporation in Bangladesh by Md Nahid Ferdous, Mohammad Ismail Hossain, Mohammed Manik

“…Several methods are now under development in many studies to monitor plastic waste through earth observation satellites. …”
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GA-TongueNet: tongue image segmentation network using innovative DiFP and MDi for stable generalization ability by Zhiyu Dong, Le Zhao, Yajun Fan, Haihua Ma, Changle Shao, Yiran Zhang, Peng Li

“…Tongue is directly or indirectly connected to many internal organs in Traditional Chinese Medicine (TCM). …”
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TransC-GD-CD: Transformer-Based Conditional Generative Diffusion Change Detection Model by Yihan Wen, Zhuo Zhang, Qi Cao, Guanchong Niu

“…Although deep-learning architectures have shown promise in addressing challenges in CD, many existing methods struggle to capture long-range dependencies and local spatial information effectively. …”
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The effects of limb position and grasped load on hand gesture classification using electromyography, force myography, and their combination. by Peyton R Young, Kihun Hong, Eden J Winslow, Giancarlo K Sagastume, Marcus A Battraw, Richard S Whittle, Jonathon S Schofield

“…Hand gesture classification is crucial for the control of many modern technologies, ranging from virtual and augmented reality systems to assistive mechatronic devices. …”
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A systematic review on sleep stage classification and sleep disorder detection using artificial intelligence by Tayab Uddin Wara, Ababil Hossain Fahad, Adri Shankar Das, Md Mehedi Hasan Shawon

“…Artificial Intelligence has made the evaluation process of sleep stages and sleep disorders classification more efficient. Many studies have focused on analyzing various datasets using advanced techniques and algorithms to improve computational ease and accuracy. …”
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Personalizing the Marketing with Artificial Intelligence (AI) by Rozhko Viktor I., Pletnova Yelyzaveta S.

“…Furthermore, AI algorithms can reproduce biases that exist in the data they are trained on. …”
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Python-Based Implementation of Metaheuristic MPPT Techniques: A Cost-Effective Framework for Solar Photovoltaic Systems in Developing Nations by Syed Majed Ashraf, M. Saad Bin Arif, Mohammed Khouj, Shahrin Md. Ayob, Muhammad I. Masud

“…Due to this, the simulation and analysis of these MPPT algorithms for developing and underdeveloped countries added an extra economic burden. …”
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Graph neural processes for molecules: an evaluation on docking scores and strategies to improve generalization by Miguel García-Ortegón, Srijit Seal, Carl Rasmussen, Andreas Bender, Sergio Bacallado

“…We examine the issue of generalization to divergent test tasks, which is a general concern of meta-learning algorithms in science, and propose strategies to alleviate it.…”
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State of affairs of tuberculosis in prison facilities: a systematic review of screening practices and recommendations for best TB control. by Natalie V S Vinkeles Melchers, Sabine L van Elsland, Joep M A Lange, Martien W Borgdorff, Jan van den Hombergh

“…Prison facilities encounter many challenges in TB screening procedures and TB control. …”
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DeepDate: A deep fusion model based on whale optimization and artificial neural network for Arabian date classification. by Nour Eldeen Mahmoud Khalifa, Jiaji Wang, Mohamed Hamed N Taha, Yudong Zhang

“…Image recognition based on deep learning algorithms can help to identify and classify the date fruit species, even in natural light.…”
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A Novel Local Binary Patterns-Based Approach and Proposed CNN Model to Diagnose Breast Cancer by Analyzing Histopathology Images by Mehmet Gul

“…The histopathology images improved with the QS-LBP method were then analyzed with the most commonly used Random Forest and Optimized Forest algorithms among machine learning algorithms. The BreaKHis dataset contains images with 40X, 100X, 200X, and 400X magnification resolutions and contains approximately 7924 images. …”
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Evaluating Binary Classifiers for Cardiovascular Disease Prediction: Enhancing Early Diagnostic Capabilities by Paul Iacobescu, Virginia Marina, Catalin Anghel, Aurelian-Dumitrache Anghele

“…Machine learning methods, particularly classification algorithms, have demonstrated their potential to accurately predict the risk of cardiovascular disease (CVD) by analyzing patient data. …”
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Guidelines for releasing a variant effect predictor by Benjamin J. Livesey, Mihaly Badonyi, Mafalda Dias, Jonathan Frazer, Sushant Kumar, Kresten Lindorff-Larsen, David M. McCandlish, Rose Orenbuch, Courtney A. Shearer, Lara Muffley, Julia Foreman, Andrew M. Glazer, Ben Lehner, Debora S. Marks, Frederick P. Roth, Alan F. Rubin, Lea M. Starita, Joseph A. Marsh

“…Abstract Computational methods for assessing the likely impacts of mutations, known as variant effect predictors (VEPs), are widely used in the assessment and interpretation of human genetic variation, as well as in other applications like protein engineering. Many different VEPs have been released, and there is tremendous variability in their underlying algorithms, outputs, and the ways in which the methodologies and predictions are shared. …”
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A Review of Approaches for Rapid Data Clustering: Challenges, Opportunities, and Future Directions by Mahnoor, Imran Shafi, Mahnoor Chaudhry, Elizabeth Caro Montero, Eduardo Silva Alvarado, Isabel de la Torre Diez, Md Abdus Samad, Imran Ashraf

“…The paper includes a brief introduction to clustering, discussing various clustering algorithms, improvements in handling various data types, and appropriate evaluation metrics. …”
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NeuroMorse: a temporally structured dataset for neuromorphic computing by Ben Walters, Yeshwanth Bethi, Taylor Kergan, Binh Nguyen, Amirali Amirsoleimani, Jason K Eshraghian, Saeed Afshar, Mostafa Rahimi Azghadi

“…This eliminates the need for a synchronisation clock and minimises power consumption when no data is present. However, many benchmarks for neuromorphic and spiking algorithms primarily focus on spatial features, neglecting the temporal dynamics that are inherent to most sequence-based tasks. …”
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A systematic review of Machine Learning and Deep Learning approaches in Mexico: challenges and opportunities by José Luis Uc Castillo, Ana Elizabeth Marín Celestino, Diego Armando Martínez Cruz, José Tuxpan Vargas, José Alfredo Ramos Leal, Janete Morán Ramírez

“…It identified that the selection and application of the algorithms rely on the study objective and the data patterns. …”
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USING ARTIFICIAL INTELLIGENCE IN OBSTETRICS TO DIAGNOSE FETAL MALFORMATIONS AND PREVENT DISEASES by Елена Валерьевна Литвинова, Оксана Владимировна Носкова

“…Significant advances in the application of artificial intelligence in obstetrics and gynecology are shown, identifying the need for further research and improvements with respect to achieving universality and improving the effectiveness of many of the models developed. It is indicated that the studies conducted have applied a significant number of mechanisms to overcome the dilemma of limited accuracy, among which the development of ensemble algorithms, the use of ultrasound videos, the incorporation of features in complementary imaging techniques and others have been applied. …”
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NDVI Prediction with RGB UAV Imagery Utilizing Advanced Machine Learning Regression Models by I. Aydin, U. G. Sefercik

“…In the literature, RGB camera-based NDVI prediction studies involving machine learning and deep learning algorithms have focused on the correlation of the results with the reference data (R²) or the model accuracy of the algorithms used. …”
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Improving accuracy of self-reported diagnoses of rheumatoid arthritis in the French prospective E3N-EPIC cohort: a validation study by Marie-Christine Boutron-Ruault, Yann Nguyen, Carine Salliot, Gaëlle Gusto, Elise Descamps

“…It will subsequently allow investigating many potential risk factors of RA in women.…”
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Microstructured Waveguide Sensors for Point-of-Care Health Screening by Svetlana S. Konnova, Pavel A. Lepilin, Anastasia A. Zanishevskaya, Alexey Y. Gryaznov, Natalia A. Kosheleva, Victoria P. Ilinskaya, Julia S. Skibina, Valery V. Tuchin

“…Biosensor technologies in medicine, as in many other areas, are replacing labor-intensive methods of monitoring human health. …”
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