APPLICATION ELEMENTS OF LITHOTHERAPY IN COMPLEX TREATMENT OF NEUROPATHY FACIAL NERVE by V.L. Melnik, V.K Shevchenko, E.V. Shevchenko, I.V. Melnik

“…As a result of the treatment algorithm applied to the first group of 11 patients (91,2%) received long-term remission of the disease. …”
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The application of blockchain with a comparative approach and its impact on risk, flexibility and internal control evaluation by mohammadsadegh aminipoor, HamidReza GholamniaRoshan, azadeh kiapour, Iman Dadashi

“…In the following, using partial least squares technique and SMART PLS software, the resulting model has been validated. …”
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Use of ICT to Confront COVID-19 by Yousry Saber El Gamal

“…<p style="text-align: justify;" align="center"><span style="text-align: justify;">The impact of COVID-19 outbreak has now become of grave concern for virtually every country in the world, and forced a majority of countries into partial or complete lockdowns. WHO reports show more than 150 Million confirmed cases, with a death toll exceeding 3 Million worldwide as of 28 April 2021. …”
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Learning-based early detection of post-hepatectomy liver failure using temporal perioperative data: a nationwide multicenter retrospective study in ChinaResearch in context by Kai Wang, Qian Yang, Kang Li, Shanhua Tang, Baoluhe Zhang, Xiangyun Liao, Shunda Du, Wenguang Fu, Zhiwei Li, Huanwei Chen, Haorong Xie, Pengxiang Huang, Jieyuan Li, Qiuting Wang, Haiqing Liu, Zhiwei Huang, Pheng Ann Heng, Xueshuai Wan, Chuanjiang Li, Weixin Si

“…Findings: Our model demonstrated high accuracy in detecting PHLF within the first 24 h after surgery, achieving an AUC of 0.952 in internal validation and 0.884 in external validation of the China cohort, outperforming other competing algorithms. In the MIMIC-IV cohort with challenging incomplete EHR data, our model had an AUC of 0.654, which was still superior to alternative algorithms, indicating generalization potential for the Western population. …”
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Runtime Scheduling, Allocation, and Execution of Real-Time Hardware Tasks onto Xilinx FPGAs Subject to Fault Occurrence by Xabier Iturbe, Khaled Benkrid, Chuan Hong, Ali Ebrahim, Tughrul Arslan, Imanol Martinez

“…These algorithms consider most of the technological constraints existing in modern partially reconfigurable FPGAs as well as spontaneously occurring faults and emerging permanent damage in the silicon substrate of the chip. …”
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METHODOLOGY AND RESULTS OF THE MAIN TECHNICAL OF PARAMETERS OF THE MANEUVERABLE UNMANNED AERIAL VEHICLE JUSTIFICATION by M. A. Kiselev

“…The greatest challenge lies in creating the algorithms, data sensors, control hardware, communications hardware, etc. necessary for utilization of an unmanned aerial vehicle (UAV). …”
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Optimization of Traffic Flow by Allowing Private Cars to Merge into the Bus Lane at Specific Locations by Zhentao Yin, Kai Yuan, Shenshen Zheng

“…We use the genetic algorithms to optimize the system. Finally, simulation results show that the partially space-shared bus lane reduces private-car delays and total delays of the system. …”
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Acoustic modelling of machines by Z. ENGEL, L. STRYCZNIEWICZ

“…Mathematical dependencies, algorithms of modelling and examples of calculation results are included in the paper.…”
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A spiking neural network model of model-free reinforcement learning with high-dimensional sensory input and perceptual ambiguity. by Takashi Nakano, Makoto Otsuka, Junichiro Yoshimoto, Kenji Doya

“…This class of problem is formally known as partially observable reinforcement learning (PORL) problems. …”
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Enhancing Autonomous Driving in Urban Scenarios: A Hybrid Approach with Reinforcement Learning and Classical Control by Rodrigo Gutiérrez-Moreno, Rafael Barea, Elena López-Guillén, Felipe Arango, Fabio Sánchez-García, Luis M. Bergasa

“…Specifically, the authors address the Decision Making problem by employing a Partially Observable Markov Decision Process formulation and offer a solution through the use of Deep Reinforcement Learning algorithms. …”
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Bayesian Prediction Intervals Based on Type-I Hybrid Censored Data from the Lomax Distribution under Step-Stress Model by Abdalla Rabie, Abd EL-Baset A. Ahmad, Mohamad A. Fawzy, Tahani A. Aloafi

“…The observed data is censored using a Type-I hybrid censoring scheme under a step-stress partially accelerated life test. There are two types of sampling schemes considered: one-sample and two-sample. …”
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Recursive GNNs for Learning Precoding Policies With Size-Generalizability by Jia Guo, Chenyang Yang

“…These merits are important for learning wireless policies under dynamic environments, which partially come from the matched permutation equivariance (PE) properties of the GNNs to the policies to be learned. …”
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Parallel art:artistic creation under human-machine collaboration by Chao GUO, Yue LU, Yilun LIN, Fan ZHUO, Fei-Yue WANG

“…The artistic creation of machine has drawn considerable attention and achieved significant development in recent years.There are more and more artworks processed partially by specific algorithms,or even created entirely by machines.Despite their popularity,it is hard for these artworks to be accepted by humans because of their underwhelming sensory impacts and lack of empathy.However,their impact is highly concerned by the art community.A theoretical framework called the parallel art system was proposed to solve the technical and human-machine-relationship challenges in artistic creation.The system aims to build a partnership between humans and machines,enabling them to collaborate in a parallel manner,and even provide a new way to integrate human emotion and machine logic.…”
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Clinical decision support for vestibular diagnosis: large-scale machine learning with lived experience coaching by Cecilia A. Callejas Pastor, Hyun Tae Ryu, Jung Sook Joo, Yunseo Ku, Myung-Whan Suh

“…The model incorporates 50 clinical features, selected through a hybrid approach combining algorithmic methods (RFE-SVM and SKB score) and expert clinical knowledge. …”
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Enhancing prediction of fluid-saturated fracture characteristics using deep learning super resolution by Manju Pharkavi Murugesu, Vignesh Krishnan, Anthony R. Kovscek

“…While past literature has offered solutions to improve resolution of CT rock images, including deep learning-based algorithms, our study uniquely focuses on improving dynamic, partially and fully fluid-saturated geological images. …”
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Design as Exploration by Ding Yang

“…In these paradigms, a design task is formulated, or partially formulated, as an optimization problem. Multi-Disciplinary Optimization and Multi-Objective Optimization, as two important optimal-design paradigms, have shown their great potential in improving the performances of complex buildings in recent decades. …”
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Knowledge and Perception of Practicing Anesthetists on Current Techniques, Clinical Applications, and Limitations of Artificial Intelligence in Anesthesiology: An Indian Study by Manasij Mitra, Maitraye Basu, Amrita Ghosh, Ranabir Pal

“…Their concepts on techniques, applications, and safety of AI including levels and potentials of use were significant so far as predictive algorithms, assessing vital parameters and perioperative care were concerned. …”
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Implementation of smart devices in health crisis scenarios: risks and opportunities by Roberto Losada Maestre, Rubén Sánchez Medero

“…Tasks such as triage, diagnosis, or determining a patient’s life-threatening risk are some of the applications we can delegate to algorithms. However, the limited number of real clinical experiences and the lack of research on its implementation mean that we only partially understand the risks involved in its development. …”
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Transforming Sleep Monitoring: Review of Wearable and Remote Devices Advancing Home Polysomnography and Their Role in Predicting Neurological Disorders by Diana Vitazkova, Helena Kosnacova, Daniela Turonova, Erik Foltan, Martin Jagelka, Martin Berki, Michal Micjan, Ondrej Kokavec, Filip Gerhat, Erik Vavrinsky

“…The paper highlights the integration of hardware innovations, targeted sleep parameters, and partially advanced algorithms, illustrating how these elements converge to provide reliable sleep health information. …”
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Analysis of disease severity and mortality prediction using machine learning during COVID-19 by Hodjat (Hojatollah) Hamidi, Mostafa Moradi

“…This paper focuses on how machine learning (ML) algorithms and applications have been used to analyze disease severity and mortality prediction in COVID-19 research. …”
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