Digital remote monitoring of people with multiple sclerosis by Michelangelo Dini, Michelangelo Dini, Giancarlo Comi, Letizia Leocani, Letizia Leocani, Letizia Leocani

“…Many studies have demonstrated their reliability not only in clinical settings and for independent execution of motor assessments by patients, but also for passive monitoring during everyday life. …”
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Machine Learning–Based Analysis of Lifestyle Risk Factors for Atherosclerotic Cardiovascular Disease: Retrospective Case-Control Study by Hye-Jin Kim, Heeji Choi, Hyo-Jung Ahn, Seung-Ho Shin, Chulho Kim, Sang-Hwa Lee, Jong-Hee Sohn, Jae-Jun Lee

“…We divided the dataset into a training and a test dataset in an 8:2 ratio. We also used bootstrapping to train the ML model with the area under the receiver operating characteristics curve score. …”
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New Challenging Systemic Therapies for Juvenile Scleroderma: A Comprehensive Review by Chiara Sassetti, Claudia Borrelli, Martha Mazuy, Cristina Guerriero, Donato Rigante, Susanna Esposito

“…Autologous stem cell transplantation (ASCT) has also been explored in severe, treatment-resistant cases, although data are extremely limited. …”
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A novel dataset and deep learning object detection benchmark for grapevine pest surveillance by Giorgio Checola, Paolo Sonego, Roberto Zorer, Valerio Mazzoni, Franca Ghidoni, Alberto Gelmetti, Pietro Franceschi

“…Additionally, we tested the impact of altering image resolution and data augmentation, while also addressing potential issues related to class detection. …”
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Forest Change Monitoring Based on Block Instance Sampling and Homomorphic Hypothesis Margin Evaluation by Wei Feng, Fan Bu, Puxia Wu, Gabriel Dauphin, Yinghui Quan, Mengdao Xing

“…Firstly, training samples in classification algorithms are typically selected through pixel-based random sampling or manual regional sampling. …”
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Abnormal heart sound recognition using SVM and LSTM models in real-time mode by Moy’awiah A. Al-Shannaq, Areen Nasrawi, Abed Al-Raouf K. Bsoul, Ahmad A. Saifan

“…Digital signal processing methods, by applying the fast Fourier transform, filtering techniques, and the dual-tree complex wavelet transform, with machine learning classification algorithms are employed to segment the input phonocardiogram signal, extract meaningful features, and find the appropriate class for the input signal. …”
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Lidargrammetric co-matching and co-adjustment – a new method of photogrammetric and LiDAR data integration by A. Rzonca, M. Twardowski

“…The proposed method necessitates the utilisation of both sets of data: The study area was imaged using both RGB and CIR technologies, with intensity LiDAR strips also employed to cover the same area. The present approach is founded upon the notion of lidargrammetry (Jayendra-Lakshman and Devarajan, 2013), which uses photogrammetric algorithms for lidar data processing (Rzonca and Twardowski, 2022).…”
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A novel approach to wind energy modeling in the context of climate change at Zaafrana region in Egypt by Bassem Khaled Kamel, Almoataz Y. Abdelaziz, Mahmoud A. Attia, Amr Khaled Khamees

“…However, the stochastic behavior of the renewable energy is also affected by the environmental conditions. In this context, The main objective of this paper is to present a novel wind energy modeling that includes the effect of ambient temperature on the wind turbine capabilities. …”
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Applicability Evaluation of Provincial Precipitation Real-time Analysis Product in Beijing by Zhao Wenfang, Wang Huiying, Meng Huifang, Miao Yupeng, Huang Mingming, Fan Min, Tang Wei

“…The same core multi-source fusion algorithms for real-time precipitation analysis products are applied in this system, allowing access to additional provincial local observations. …”
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Will AI “Subtly” Take Over Decision-making in the EU Migration Context? Warnings and Lessons from ETIAS and VIS by Lorenzo Gugliotta, Abdullah Elbi

“…Conclusions | (Abstract) In 2019, the EU laid down the groundwork for interoperability in the Area of Freedom, Security and Justice, envisaging the use of algorithmic tools that can qualify as AI systems under the AI Act. …”
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Spectral divergence prioritizes key classes, genes, and pathways shared between substance use disorders and cardiovascular disease by Everest Castaneda, Everest Castaneda, Elissa Chesler, Erich Baker

“…Gene networks associated with SUDs also implicate additional biological pathways and may be used to stratify disease subtypes. …”
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Development of the mechanism of intellectual management of “student-lecturer” relations in the space of virtual education with the use of neural networks by Guseyn Alekper ogly Gasymov

“…Studies show that for traditional universities there are different approaches with the use of expert systems, genetic algorithms to solve thisDevelopment of the mechanism of intellectual management of “student-lecturer” relations  in the space of virtual education with the use of neural networks problem. …”
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Applications of AI-Based Models for Online Fraud Detection and Analysis by Antonis Papasavva, Samantha Lundrigan, Ed Lowther, Shane Johnson, Enrico Mariconti, Anna Markovska, Nilufer Tuptuk

“…Furthermore, we conclude that the evolving nature of scams limits the effectiveness of models trained on outdated data. We also identify that researchers often omit discussions of the limitations of their data or training biases. …”
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Advancement in public health through machine learning: a narrative review of opportunities and ethical considerations by Sumit Singh Dhanda, Deepak Panwar, Chia-Chen Lin, Tarun Kumar Sharma, Deependra Rastogi, Shantanu Bindewari, Anand Singh, Yung-Hui Li, Neha Agarwal, Saurabh Agarwal

“…Ethically, this review surfaces critical issues, including algorithmic bias, data privacy concerns in mental health analytics, and the interpretability of black-box models used in outbreak surveillance. …”
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USE OF METHODOLOGICAL TASKS IN PROFESSIONAL TRAINING OF FUTURE TEACHERS OF INFORMATICS by Nataliia S. Pavlova

“…The methodological task integrates the main elements of methodological activity concerning planning and designing of educational process and its management by the teacher, and also predicts educational and cognitive actions of pupils. …”
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Comparing interpretable machine learning models for fall risk in middle-aged and older adults with and without pain by Shangmin Chen, Yongshan Gao, Lin Du, Mengzhen Min, Lei Xie, Liping Li, Xiaodong Chen, Zhigang Zhong

“…Abstract Pain is common in middle-aged and older adults, has also been identified as a fall risk factor, whereas the mechanism of falls in pain is unclear. …”
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Investigation of the Contribution of Five Broadcast Ionospheric Models (GPSK, NTCMG, NEQG, BDGIM, and BDSK) and IRTG to GNSS Positioning During Different Solar Activities in Solar... by Min Li, Yunbin Yuan, Ting Zhang, Hanying Xu, Xingliang Huo, Wenyao Zhang

“…Consequently, ionospheric correction algorithms (ICAs) are also essential for low‐cost DF devices in hybrid‐frequency positioning. …”
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Predicting ICU mortality in heart failure patients based on blood tests and vital signs by Yeao Wang, Jianke Rong, Zhili Wei, Xiaoyu Bai, YunDan Deng

“…In contrast, blood tests are not only simpler but also reflect the overall health status of the body. …”
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Comparison of light gradient boosting and logistic regression for interactomic hub genes in Porphyromonas gingivalis and Fusobacterium nucleatum-induced periodontitis with Alzheime... by Pradeep Kumar Yadalam, Shubhangini Chatterjee, Prabhu Manickam Natarajan, Carlos M. Ardila, Carlos M. Ardila

“…Aggregatibacter actinomycetemcomitans and Fusobacterium nucleatum may also play a role in the development of Alzheimer's disease. …”
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Acoustic emission detection and defect identification method for micro-leakage in natural gas pipeline valves by Lizhen ZHANG, Wen'ao WANG

“…This approach not only offers monitoring means but also establishes safeguard measures crucial for ensuring the secure operation of natural gas pipeline systems.…”
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