Generative AI Models in Time-Varying Biomedical Data: Scoping Review by Rosemary He, Varuni Sarwal, Xinru Qiu, Yongwen Zhuang, Le Zhang, Yue Liu, Jeffrey Chiang

“…Recent advances in generative artificial intelligence (AI) have provided powerful tools to represent complex distributions and patterns with minimal underlying assumptions, with major impact in fields such as finance and environmental sciences, prompting researchers to apply these methods for disease modeling in health care. …”
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Automatic Detection and Correction of Detuned Singing System for Use With Query-By-Humming Applications by Michał LECH

“…The common approach to searching for a requested song basing on the melody retrieved from hummed pattern usually employs the so-called Parsons code or melody contour. …”
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Social Media and Men’s Health: Separating Science from Speculation in Andrology by Michael George, Vaibhav Modgil, Ian Pearce, Theodora Stasinou

“…Amongst posts, there has been a shift towards highly engaging short-form video content, which is particularly popular with young adults. Social media algorithms reinforce consumption patterns by continuously delivering content based on user engagement: the more an individual interacts with a topic or creator, the more related content appears, creating a self-sustaining feedback loop; this principle underpins the concept of virality and risks the rapid dissemination of inaccuracies online. …”
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A data-driven group retrosynthesis planning model inspired by neurosymbolic programming by Xuefeng Zhang, Haowei Lin, Muhan Zhang, Yuan Zhou, Jianzhu Ma

“…Our investigation reveals reusable synthesis patterns that augment the reaction template library, resulting in progressively decreasing marginal inference time as the algorithm processes more molecules. …”
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Adapting Vision Transformer-Based Object Detection Model for Handwritten Text Line Segmentation Task by Osman Furkan KARAKUŞ, Ayla GULCU, Ali Can KARACA

“…For a diverse set of baselines methods, we have also implemented two learning-free algorithms such as A* Search Algorithm and the Genetic Algorithm (GA). …”
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ANALISIS OF THE INFLUENCE OF THE MAIN PARAMETERS AND CONDITION OF WORK OF AIRCRAFT CESN ON THE EFFICENCY OF THEIR USE METHODS OF MATHEMATICAL MODELING by V. I. Troitsky

“…The operation of the maximum search was made up of two procedures: searching for the global maximum area of the correlation matrix by enumerating all matrix entries and refining the location of the true maximum point by quadratic interpolation of the function. …”
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HARDWARE AND SOFTWARE COMPLEX FOR FUNCTIONAL STATE MONITORING OF MOTHER AND FETUS by I. V. Tolmachyov, K. S. Brazovsky, A. S. Tsverova, V. S. Ripenko

“…At first stage the fetal cardiointervalogram (i.e. fetus heartbeat period and the distribution pattern of these intervals in time) was studied. Second stage was carried out to search additional criteria of fetal functional state assessment with placental insufficiency in the pregnant with hyperandrogenism in the third trimester.As result, it was defined, that parameters of heart rate structure at 32–35 weeks of gestation allows to assess the risk of functional disorders and development of fetus hypoxia with sensitivity Se = 80% and specificity Sp = 73%.…”
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Prediction of obesity levels based on physical activity and eating habits with a machine learning model integrated with explainable artificial intelligence by Yasin Görmez, Fatma Hilal Yagin, Burak Yagin, Yalin Aygun, Hulusi Boke, Georgian Badicu, Matheus Santos De Sousa Fernandes, Abedalrhman Alkhateeb, Mahmood Basil A. Al-Rawi, Mohammadreza Aghaei, Mohammadreza Aghaei

“…The results also highlighted age, weight, height and specific food patterns as key predictors of obesity. In terms of interpretability, LIME showed superior in fidelity, whereas SHAP showed improved sparsity and consistency across models, facilitating a comprehensive understanding of trait importance.ConclusionThis research demonstrates that ML algorithms, when integrated with XAI technologies, can accurately predict obesity levels and explain important contributing risk factors. …”
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Advancements in deep learning for early diagnosis of Alzheimer’s disease using multimodal neuroimaging: challenges and future directions by Muhammad Liaquat Raza, Muhammad Liaquat Raza, Muhammad Liaquat Raza, Syed Tawassul Hassan, Subia Jamil, Noorulain Hyder, Kinza Batool, Sajidah Walji, Muhammad Khizar Abbas

“…These models can effectively process structural and functional imaging modalities, extracting relevant features and patterns associated with Alzheimer’s pathology. Integration of multiple imaging modalities has demonstrated improved diagnostic accuracy compared to single-modality approaches. …”
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Optimized Identity Authentication via Channel State Information for Two-Factor User Verification in Information Systems by Chuangeng Tian, Fanjia Li, Xiaomeng Liu, Juanjuan Li

“…For classification, a kernel support vector machine (SVM) model is trained using a randomized hyperparameter search algorithm. The SVM classifies the CSI feature patterns obtained from user-specific keystroke dynamics, which are processed by Hampel filtering, Butterworth low-pass filtering, wavelet transform threshold denoising, a dual-threshold moving window detection algorithm, a subcarrier selection method, and PCA, to achieve optimal performance. …”
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Impact of the STFT Window Size on Classification of Grain-Oriented Electrical Steels from Barkhausen Noise Time–Frequency Spectrograms via Deep CNNs by Michal Maciusowicz, Grzegorz Psuj

“…Due to the automation of the search for diagnostic patterns, the stage of selecting transformation parameters becomes extremely important in the process of preparing training data for evaluation algorithms. …”
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Artificial intelligence applied to the study of human milk and breastfeeding: a scoping review by Sergio Agudelo-Pérez, Daniel Botero-Rosas, Laura Rodríguez-Alvarado, Julián Espitia-Angel, Lina Raigoso-Díaz

“…Prediction of exclusive breastfeeding patterns: AI models, such as decision trees and machine learning algorithms, identify factors influencing breastfeeding practices, including maternal experience, hospital policies, and social determinants, highlighting actionable predictors for intervention. 2. …”
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Methodology for Studying Neural Network Descriptors in Solving the Problem of Finding Anatomical Layers in Computed Tomography Images of the Lungs by A. A. Kosareva

“…Using the proposed algorithm, the neural network search result for anatomical patterns, expressed in mm to the searched layer, was improved by 47 % for the first ten heart-class images found and by 18 % for images with positions from 10 to 100. …”
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Constructing a web recommender system using web usage mining and user’s profiles by T. Mombeini, A. Harounabadi, J. Rezaeian Sheshdeh

“…Web usage mining was designed to function on web server records, which are included in user search results. Therefore, recommender servers use the web usage mining technique to predict users’ browsing patterns and recommend those patterns in the form of a suggestion list. …”
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Electromagnetic target detection model for unmanned aerial vehicle platforms based on Bayesian detection by DENG Wenjie, CHEN Song, WU Di, LIU Kaiyue, XU Ziliang, HE Runze

“…The performance of the novel model is derived and analyzed under a scanning coverage search algorithm. Analytical and simulation results indicate that the proposed model effectively describes the process of electromagnetic target detection. …”
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Research on Gamma Image Reconstruction Method Based on Multi-distance System Matrix Superposition by WU Yuan1, 2, , XU Feng1, 2, , ZHOU Yicong1, 2, XIAO Yufeng1, 2, ZHENG Yulai3

“…Since gamma rays have higher penetrating power and longer action distance than α particles and β rays, they can affect a larger area and have radiation effects on various substances in the environment. Therefore, the search and positioning of radioactive sources has always been the focus of radioactive source search. …”
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Enhanced Detection of Intrusion Detection System in Cloud Networks Using Time-Aware and Deep Learning Techniques by Nima Terawi, Huthaifa I. Ashqar, Omar Darwish, Anas Alsobeh, Plamen Zahariev, Yahya Tashtoush

“…We generate real DoS traffic, including normal, Internet Control Message Protocol (ICMP), Smurf attack, and Transmission Control Protocol (TCP) classes, and develop nine predictive algorithms, combining traditional machine learning and advanced deep learning techniques with optimization methods, including the synthetic minority sampling technique (SMOTE) and grid search (GS). …”
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Innovative approaches for skin disease identification in machine learning: A comprehensive study by Kuldeep Vayadande, Amol A. Bhosle, Rajendra G. Pawar, Deepali J. Joshi, Preeti A. Bailke, Om Lohade

“…Machine learning has become a potent tool in the search for more precise and effective diagnostic techniques because of its capacity to analyze enormous volumes of data and identify intricate patterns. …”
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Review: Multiobject tracking in livestock − from farm animal management to state-of-the-art methods by M.H. Nidhi, K. Liu, K.J. Flay

“…Key challenges that need to be addressed include frequent occlusions and complex, non-linear motion patterns that are characteristic of livestock behaviour. …”
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Integrating Metaheuristics and Machine Learning for Enhanced Vehicle Routing: A Comparative Study of Hyperheuristic and VAE-Based Approaches by Kassem Danach, Louai Saker, Hassan Harb

“…To tackle this challenge, the proposed metaheuristic-based hyperheuristic dynamically selects and adapts low-level heuristics using Simulated Annealing (SA) and Ant Colony Optimization (ACO), enhancing search efficiency and solution quality. In contrast, the VAE-based approach leverages deep learning to model historical routing patterns and autonomously generate new heuristics tailored to problem-specific characteristics. …”
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