The Value of Biomarkers in the Diagnosis and Prognosis of Heart Failure in Older Age by V. N. Larina, V. I. Lunev

“…The search for reliable algorithms for diagnosing heart failure with preserved left ventricular ejection fraction (LVEF) in elderly patients is an urgent problem due to the low specificity of clinical manifestations and the peculiarities of involutive processes occurring in the human body. …”
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Vehicle Detection and Shape Refinement Based on LiDAR by YU An, HU Dongfang, WANG Xuepeng, ZHANG Jin, ZHOU Yan, XIE Guotao, QIN Xiaohui, HU Manjiang

“…Accurate vehicle detection and shape estimation can provide accurate static information for follow-up tracking and prediction. Although the existing vehicle detection algorithm based on lidar can accurately detect and classify each target vehicle, there is a problem of unstable estimation when the vehicle point cloud contour is partially obscured in an "L" shape. …”
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Emotional intelligence in management activities аnd artificial intelligence technologies by M. S. Laschenov, R. A. Bondarenko, I. V. Slomova

“…The article examines the role of emotional intelligence (emotional quotient) in the process of management activities and the competing position of artificial intelligence (hereinafter referred to as AI), which is trying to master it through learning algorithms and implementation in management practice. …”
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Retinal revelations: Seeing beyond the eye with artificial intelligence by John Davis Akkara

“…AI-powered analysis of these images can predict systemic diseases such as Alzheimer’s, Parkinson’s, cardiovascular disease, cerebrovascular disease, chronic kidney disease, and liver disease. …”
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Lightweight opportunistic routing forwarding strategy based on Markov chain by Feng LI, Ya-li SI, Zhen CHEN, Li-min SHEN

“…A lightweight opportunistic routing forwarding strategy (MOR) was proposed based on Markov chain.In the scheme,the execute process of network was divided into a plurality of equal time period,and the random encounter state of node in each time period was represented by activity degree.The state sequence of a plurality of continuous time period constitutes a discrete Markov chain.The activity degree of encounter node was estimated by Markov model to predict its state of future time period,which can enhance the accuracy of activity degree estimation.Then,the method of comprehensive evaluating forwarding utility was designed based on the activity degree of node and the average encounter interval.MOR used the utility of node for making a routing forwarding decision.Each node only maintained a state of last time period and a state transition probability matrix,and a vector recording the average encounter interval of nodes.So,the routing forwarding decision algorithm was simple and efficient,low time and space complexity.Furthermore,the method was proposed to set optimal number of the message copy based on multiple factors,which can effectively balance the utilization of network resources.Results show that compared with existing algorithms,MOR algorithm can effectively increase the delivery ratio and reduce the delivery delay,and lower routing overhead ratio.…”
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Artificial intelligence-driven metabolic engineering is applied to the development of active ingredients in Traditional Chinese Medicine by Zhang Guoqi, Wang Juan

“…In this paper, we introduce AI-driven machine learning algorithms in prediction models, and also review recent research progress on AI-assisted metabolic engineering design and production of high-value compounds, focusing on how to use AI methods to achieve directed evolution of strains.…”
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A New Privacy-Preserving Scheme for Continuous Query in Location-Based Social Networking Services by Eric Ke Wang, Yunming Ye

“…In this paper, we analyze the existing location privacy protection systems and algorithms for location based services; considering their disadvantages of slow responding time and high anonymization costs, we propose a new enhanced greedy cloaking algorithm which predicts a cloaking area at the initial query to be the cloaking region in the whole query lifetime by the comprehensive computation of privacy monitor, quality monitor, and dynamic adjuster. …”
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BCAST IDS: A Novel Network Intrusion Detection System for Broadcast Networks by Javier Gombao

“…A modern approach to enhancing the capabilities of NIDSs is the use of machine learning (ML) algorithms that predict attacks based on data. This study introduces a novel and lightweight NIDS called Broadcast IDS (BCAST IDS) that uses specific network traffic patterns and the Isolation Forest algorithm to detect anomalies in broadcast networks. …”
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Optimised Implant Selection Using Digital Volume Tomography (DVT) Osteodensitometry by Manfred Nilius, Jörg Winterhoff

“…At the same time, the point at which loading occurs can already be defined at the planning stage, thanks to the predictable primary stability. A standard integration of DVT osteodensitometry in the algorithms of implant planning software thus seems desirable.…”
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AI-Based Breast Cancer Detection System: Deep Learning and Machine Learning Approaches for Ultrasound Image Analysis by Amro Moursi, Abdulrahman Aboumadi, Uvais Qidwai

“…Furthermore, our integration of these algorithms into a user-friendly MATLAB R2024b application ensures easy access for medical professionals, facilitating timely diagnosis and treatment. …”
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Immune-Mediated Adverse Events Associated with Ipilimumab CTLA-4 Blockade Therapy: The Underlying Mechanisms and Clinical Management by Ahmad Tarhini

“…Implementation of these irAE management algorithms will help ensure that patients are able to benefit from ipilimumab therapy with adequate control of toxicities.…”
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Hybrid Laminar Flow Control Optimizations for Infinite Swept Wings by Yayun Shi, Xiayu Lan, Tihao Yang

“…The Reynolds-averaged Navier-Stokes (RANS) solver coupled with the linear stability theory is applied for the laminar-turbulent transition prediction, and the traditional optimization method based on evolutionary algorithms is applied for laminar flow wing optimization. …”
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Improving pediatric care in Uganda with a digital platform and quality improvement initiative: A retrospective review of Smart Triage + QI. by Rebecca Goertzen, Yashodani Pillay, James Karugaba, Ivan Aine Aye Ishebukara, Ahmad Asdo, Dustin Dunsmuir, Justine Behan, Charly Huxford, Stefanie K Novakowski, Fredson Tusingwire, Ronald Kasyaba, Gloria Kakuru, John Khisa, Stephen Businge, Mike Kyewalyanga, Niranjan Kissoon, J Mark Ansermino

“…<h4>Methods</h4>Smart Triage is a risk prediction algorithm and digital platform that enables healthcare workers to triage patients and track treatments effectively. …”
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A multimodal MRI-based machine learning framework for classifying cognitive impairment in cerebral small vessel disease by Guihan Lin, Weiyue Chen, Yongkang Geng, Bo Peng, Surui Liu, Minjiang Chen, Chunying Pang, Pengjun Chen, Chenying Lu, Zhihan Yan, Shuiwei Xia, Yakang Dai, Jiansong Ji

“…Our study provides a multimodal MRI-based machine learning framework, utilizing the AutoGluon platform, that outperforms traditional algorithms in classifying MCI and NCI, offering a promising tool for the early prediction of MCI in CSVD.…”
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Bionic Compass Method Based on Atmospheric Polarization Optimization in Non-Ideal Clear Condition by Yuyang Li, Xia Wang, Min Zhang, Ruiqiang Li, Qiyang Sun

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GRRIS: A Real-time Intrasite Observation Scheduling Scheme for Distributed Survey Telescope Arrays by Yajie Zhang, Ce Yu, Chao Sun, Yi Hu, Zhaohui Shang, Jizeng Wei, Xu Yang

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Forecasting Surface Velocity Fields Associated With Laboratory Seismic Cycles Using Deep Learning by G. Mastella, F. Corbi, J. Bedford, F. Funiciello, M. Rosenau

“…Using data from two types of experiments, we explore the prediction performances of multiple Deep Learning (DL) and ML algorithms. …”
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A Hybrid Approach to Call Admission Control in 5G Networks by Mohammed Al-Maitah, Olena O. Semenova, Andriy O. Semenov, Pavel I. Kulakov, Volodymyr Yu. Kucheruk

“…Such artificial intelligence techniques as neural networks, fuzzy systems, and genetic and evolutionary algorithms are widely used for communication systems management, optimization, and prediction. …”
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Transformer-based long-term predictor of subthalamic beta activity in Parkinson’s disease by Salvatore Falciglia, Laura Caffi, Claudio Baiata, Chiara Palmisano, Ioannis Ugo Isaias, Alberto Mazzoni

“…Our study paves the way for remote monitoring strategies and the implementation of new algorithms for personalized auto-tuning aDBS devices.…”
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Comprehensive assessment on estimating the thermodynamic and mechanical properties of multicomponent Fe–Cr-based alloys using machine learning techniques by Ahed Habib, Bashar Alibrahim, Mahdi Z. Alnunu, Hussein Moussa, Maan Habib

“…This study investigates the performance of 11 different machine learning algorithms to predict the mixing enthalpy, Young’s modulus, and the shear-to-bulk modulus ratio of Fe–Cr alloys with additions of Ni, Mo, Al, W, V, and Nb. …”
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