Unraveling genetic predisposition and oxidative stress in vitiligo development and the role of artificial intelligence (AI) in diagnosis and management by Kocić Hristina, Lotti Torello, Jevtović-Stoimenov Tatjana, Wollina Uwe, Valle Yan, Lukić Stevo, Klisić Aleksandra

“…By analysing vast datasets, AI algorithms can identify patterns within complex genetic markers and clinical features, facilitating earlier and more precise detection of vitiligo. …”
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A New Approach for Determination of Seed Distribution Area in Vertical Plane by Alper Gülbe, Sefa Altıkat

“…For this purpose, the different calculation methods of seed distribution area namely, standard deviational ellipse, voronoi polygons with delaunay triangulation, integral method, and developed one, the concave hull algorithm was considered and compared in this study. …”
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Classification algorithm of loin swarm optimization kernel extreme learning machine by Liu Xinjian, Sun Zhonghua

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Automated Recognition of Abnormalities in Gastrointestinal Endoscopic Images – Evaluation of an AI Tool for Identifying Polyps and Other Irregularities by Weronika Jarych, Elżbieta Tokarczyk, Patryk Iglewski, Daria Ziemińska, Karina Motolko, Rafał Burczyk, Konrad Duszyński, Michał Kociński, Jan Reinald Wendt

“…Key advantages of AI integration in endoscopy include improved sensitivity, minimized detection errors, and the potential to optimize clinical workflow efficiency. …”
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AI Efficiency in Dentistry: Comparing Artificial Intelligence Systems with Human Practitioners in Assessing Several Periodontal Parameters by Oana-Maria Butnaru, Monica Tatarciuc, Ionut Luchian, Teona Tudorici, Carina Balcos, Dana Gabriela Budala, Ana Sirghe, Dragos Ioan Virvescu, Danisia Haba

“…However, further validation in clinical settings is necessary to address limitations such as algorithmic bias and atypical cases. AI integration in dentistry can enhance diagnostic precision and patient outcomes while reducing variability in clinical assessments.…”
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Performance comparison of different algorithms to secure the information for Wireless sensor Network by El Gatte Oumayma, El Abbassi Ahmed, Mouhib Omar, Tilioua Amine

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AI-powered topic modeling: comparing LDA and BERTopic in analyzing opioid-related cardiovascular risks in women by Li Ma, Li Ma, Ru Chen, Weigong Ge, Paul Rogers, Beverly Lyn-Cook, Huixiao Hong, Weida Tong, Ningning Wu, Wen Zou

“…Our findings indicated that AI algorithms could augment both traditional and contemporary topic modeling techniques. …”
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Fractional-order boundary value problems solutions using advanced numerical technique by Asmat Batool, Imran Talib, Muhammad Bilal Riaz

“…These operational matrices enable us to integrate monomial terms into the algorithm, effectively converting the problem into easily solvable Sylvester-type equations. …”
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Machine Learning in Ambient Assisted Living for Enhanced Elderly Healthcare: A Systematic Literature Review by Aabid A. Mir, Ahmad S. Khalid, Shahrulniza Musa, Mohammad Faizal Ahmad Fauzi, Normy Norfiza Abdul Razak, Tong Boon Tang

“…The review methodically analyzes articles and papers from the year 2020, selected based on their relevance to AAL technologies, their use of ML algorithms, and their focus on elderly care. The findings reveal the need for interpretability in AI-driven decisions and the role of GenAI in synthetic data generation and personalized conversational assistants. …”
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Multiple Channel Integration Quality Assessment Method Using NARX by Xiaolei Wang, Yingzhao He

“…Then, this study uses the dataset preprocessed with the GRA algorithm for training the NARX model. Then, this study uses the trained model to evaluate the quality of multiple channel integration comprehensively. …”
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A highly generalized federated learning algorithm for brain tumor segmentation by Jun Wen, Xiusheng Li, Xin Ye, Xiaoli Li, Hang Mao

“…Federated Learning (FL) enables collaborative model training across institutions while safeguarding sensitive patient data. The integration of these technologies holds significant potential for advancing artificial intelligence (AI) in healthcare. …”
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Developing personalized algorithms for sensing mental health symptoms in daily life by Adela C. Timmons, Abdullah Aman Tutul, Kleanthis Avramidis, Jacqueline B. Duong, Kayla E. Carta, Sierra N. Walters, Grace A. Jumonville, Alyssa S. Carrasco, Gabrielle F. Freitag, Daniela N. Romero, Matthew W. Ahle, Jonathan S. Comer, Shrikanth S. Narayanan, Ishita P. Khurd, Theodora Chaspari

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AI-driven data fusion modeling for enhanced prediction of mixed-mode I/III fracture toughness by Anantaya Timtong, Atthaphon Ariyarit, Wanwanut Boongsood, Prasert Aengchuan, Attasit Wiangkham

“…By employing adaptive boosting and general regression neural network algorithms, the models developed in this research demonstrate a marked improvement in predictive performance compared to traditional primary source models. …”
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Fast and Accurate Sperm Detection Algorithm for Micro-TESE in NOA Patients by Mahmoud Mohamed, Konosuke Kachi, Kohei Motoya, Masashi Ikeuchi

“…Methods: We present SD-CLIP (Sperm Detection using Classical Image Processing), a lightweight, real-time algorithm that simulates sperm structure detection from unstained DIC images. …”
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Advancing smart aquaculture: Cost-efficient strategies for climbing perch cultivation using AI-based models by Kosit Sriputhorn, Achara Jutagate, Surasak Matitopanum, Rungwasun Kraiklang, Rapeepan Pitakaso, Chakat Chueadee, Sarayut Gonwirat

“…By integrating Taguchi experimental design with reinforcement learning and metaheuristic algorithms, the model identifies critical environmental and operational parameters that influence fish growth and economic outcomes. …”
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Establishing strength prediction models for low-carbon rubberized cementitious mortar using advanced AI tools by Fu Limei, Xu Feng

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Breeding of Solanaceous Crops Using AI: Machine Learning and Deep Learning Approaches—A Critical Review by Maria Gerakari, Anastasios Katsileros, Konstantina Kleftogianni, Eleni Tani, Penelope J. Bebeli, Vasileios Papasotiropoulos

“…This review discusses the potential of artificial intelligence (AI), particularly machine learning (ML) and its subset, deep learning (DL), in advancing the genetic improvement of Solanaceous crops. …”
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AI-Driven Advances in Parkinson’s Disease Neurosurgery: Enhancing Patient Selection, Trial Efficiency, and Therapeutic Outcomes by José E. Valerio, Guillermo de Jesús Aguirre Vera, Maria P. Fernandez Gomez, Jorge Zumaeta, Andrés M. Alvarez-Pinzon

“…These innovations improve trial efficiency, broaden treatment options, and enhance patient outcomes. However, integrating AI into clinical trial frameworks presents challenges such as data standardization, regulatory hurdles, and the need for extensive validation. …”
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Harnessing AI and Quantum Computing for Revolutionizing Drug Discovery and Approval Processes: Case Example for Collagen Toxicity by David Melvin Braga, Bharat Rawal

“… AbstractArtificial intelligence (AI) and quantum computing will change the course of new drug discovery and approval. …”
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GLOBE Observer: A Case Study in Advancing Earth System Knowledge with AI-Powered Citizen Science by Peder V. Nelson, Russanne Low, Holli Kohl, David Overoye, Di Yang, Xiao Huang, Sriram Chellappan, Farhat Binte Azam, Ryan M. Carney, Monika Falk, Joan Garriga, Larisa Schelkin, Rebecca Boger, Theresa Schwerin

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