Artificial Intelligence in Diagnosis of Heart Failure by Yuji Xie, Linyue Zhang, Wei Sun, Ye Zhu, Zisang Zhang, Leichong Chen, Mingxing Xie, Li Zhang

“…In this review, we explore the challenges in current diagnosis of HF, basic AI concepts and common AI algorithms, and latest AI research in HF diagnosis.…”
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Hormonal and metabolic disorders in connective tissue dysplasia by I. D. Bespalova, Z. S. Chomaeva, A. V. Teteneva, Yu. I. Koshchavtseva, U. M. Mitrichenko, D. S. Romanov, S. V. Nesterovich, D. V. Poljakova, E. B. Bukreeva, T. V. Sorokina, E. V. Kalyuzhina, K. F. Tetenev, A. I. Karzilov, P. E. Mesko, V. V. Boyarko, G. E. Chernogoryuk, G. M. Chernyavskaya

“…The lecture considers the results of research conducted by Russian and foreign scientists concerning the characteristics of all types of metabolic disorders and hormonal imbalance in undifferentiated connective tissue dysplasia (CTD). …”
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Open Fractures – Time from Trauma to Efficient Surgical Debridement Is the Key Factor for Post-Traumatic Infection by Olivera Lupescu, Mihail Nagea, Alexandru Lisias Dimitriu, Nicolae Marian Ciurea, Alina Grosu, Gheorghe Ion Popescu

“…That is why medical research is directed to establishing the most effi cient diagnostic and therapeutic algorithms able to decrease the incidence of septic complications and promote optimal fracture healing. …”
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Multimodal data integration in early-stage breast cancer by Arnau Llinas-Bertran, Maria Butjosa-Espín, Vittoria Barberi, Jose A. Seoane

“…We examined the primary challenges and opportunities of these multimodal data integration algorithms, including their advantages, limitations, and critical considerations for future research. …”
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Integrated machine learning and bioinformatic analysis of mitochondrial-related signature in chronic rhinosinusitis with nasal polyps by Bo Yang, MMed, Min Gu, MMed, Chen Hong, MMed, Xin-Yuan Zou, MMed, Jia-Qi Zhang, MBBS, Ye Yuan, MBBS, Chang-Yu Qiu, MD, MSc, Mei-Ping Lu, MD, PhD, Lei Cheng, MD, PhD

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Update on Practical Management of Early-Stage Non-Small Cell Lung Cancer (NSCLC): A Report from the Ontario Forum by Parneet K. Cheema, Paul F. Wheatley-Price, Matthew J. Cecchini, Peter M. Ellis, Alexander V. Louie, Sara Moore, Brandon S. Sheffield, Jonathan D. Spicer, Patrick James Villeneuve, Natasha B. Leighl

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Machine learning prediction of obesity-associated gut microbiota: identifying Bifidobacterium pseudocatenulatum as a potential therapeutic target by Hao Wu, Yuan Li, Yuxuan Jiang, Xinran Li, Shenglan Wang, Changle Zhao, Changle Zhao, Ximiao Yang, Baocheng Chang, Juhong Yang, Juhong Yang, Jianjun Qiao, Jianjun Qiao

“…BackgroundThe rising prevalence of obesity and related metabolic disorders highlights the urgent need for innovative research approaches. Utilizing machine learning (ML) algorithms to predict obesity-associated gut microbiota and validating their efficacy with specific bacterial strains could significantly enhance obesity management strategies.MethodsWe leveraged gut microbiome data from 1,563 healthy individuals and 2,043 overweight patients sourced from the GMrepo database. …”
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A computational approach and software package RNAexploreR for grouping RNA molecules of human genes by exon features by M. M. Yatskou, V. V. Skakun, V. V. Grinev

“…A certain part of the research is aimed at developing reliable prediction models for global exon combinatorics during the formation of mature RNA. …”
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Data acquisition of exercise and fitness pressure measurement based on artificial intelligence technology by Ru Liu, Wenxi Shen

“…The IPM-EFPM system gathers data from wearable sensors, uses real-time location systems, and employs artificial intelligence's Long Short-Term Memory (LSTM) and machine learning algorithms to uncover new insights in healthcare and sports. …”
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Heart Rate Detection and Classification from Speech Spectral Features Using Machine Learning by Mohammed USMAN, Mohammed ZUBAIR, Zeeshan AHMAD, Monji ZAIDI, Thafasal IJYAS, Muneer PARAYANGAT, Mohd WAJID, Mohammad SHIBLEE, Syed Jaffar ALI

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Revolutionizing Education: Harnessing Machine Learning and Deep Learning for Digital Examination Transformation by Shilpi Gautam, Asadi Srinivasulu

“…One prominent challenge pertains to the development of ethical and impartial assessment algorithms. With the integration of machine learning and deep learning methods into digital examinations, concerns related to assessment bias and fairness have surfaced, necessitating research to design algorithms capable of delivering unbiased evaluations for students from diverse backgrounds. …”
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Passive sonar with cylindrical array by J. Marszal, W. Leśniak, R. Salamon, A. Jedel, K. Zachariasz

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AI-Based Enhancing of xBn MWIR Thermal Camera Performance at 180 Kelvin by Michael Zadok, Zeev Zalevsky, Benjamin Milgrom

“…This study explores the potential of extending the operating temperature of these cameras to 180 Kelvin, leveraging advanced AI algorithms to mitigate the increased thermal noise expected at higher temperatures. …”
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A Survey on Gain-Scheduled Control and Filtering for Parameter-Varying Systems by Guoliang Wei, Zidong Wang, Wangyan Li, Lifeng Ma

“…Finally, conclusions are drawn and several potential future research directions are outlined.…”
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Artificial Intelligence Implementation in Library Information Systems: Current Trends and Future Studies by Albertoes Pramoekti Narendra, Christine Dewi, Lanyta Setyani Gunawan, Ambrosius Sindu Ardi

“…This study examines recent advancements in AI integration within LIS over the past five years, focusing on the methodologies, tools, and algorithms used. Through a systematic literature review, the study identifies key trends, challenges, and examples of AI applications in LIS, providing insights and recommendations for future research and implementation.…”
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ANALYSIS OF NEW CHAOTIC MAP AND PERFORMANCE EVALUATION IN ITS APPLICATION TO DIGITAL COLOR IMAGE ENCRYPTION by Ita Mar'atu Solihat, Suryadi MT, Yudi Satria

“…In this research a new chaotic map which is a modification from composition of MS map and Improved logistics map is proposed. …”
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Latest Advancements in Credit Risk Assessment with Machine Learning and Deep Learning Techniques by Soni Umangbhai, Jethava Gordhan, Ganatra Amit

“…The goal is to help develop novel algorithms that outperform existing methods. Even a slight improvement in defaulter prediction rates could significantly influence society by saving millions for lenders.…”
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Machine-Learning Insights from the Framingham Heart Study: Enhancing Cardiovascular Risk Prediction and Monitoring by Emi Yuda, Itaru Kaneko, Daisuke Hirahara

“…Some machine-learning algorithms were applied to multiple machine-learning models. …”
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University proceedings. Volga region. Technical sciences by V.I. Volchikhin, A.I. Ivanov, A.V. Bezyaev, I.A. Filipov

Simulation Analysis of Temperature Field of Optical Fiber Composite Overhead Ground Wire by Lifeng ZHANG, Xiaohua LI, Wenbin ZHAO

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