Remote, smart telemonitoring of COVID-19 survivors for early detection of deterioration in cardiac health (the PARTMO study) by Josephine Sau Fan Chow, Josephine Sau Fan Chow, Josephine Sau Fan Chow, Josephine Sau Fan Chow, Josephine Sau Fan Chow, Nutan Maurya, Nutan Maurya, Susan San Miguel, Rumbidzai Teramayi, Ahilan Parameswaran, Annamarie D’Souza, Gregory Melbourne, Joseph Descallar, Young Juhn, Enoch Chan, Jerome Pong

“…Thirteen patients (32.5%) were detected by the AI algorithms from the S-Patch EX monitoring system to have cardiac arrhythmias, including atrial fibrillation, supraventricular tachycardia, and ventricular tachycardia. …”
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A Survey on Anti-Money Laundering Techniques in Blockchain Systems by Leyuan Liu, Xiangye Li, Tian Lan, Yakun Cheng, Wei Chen, Zhixin Li, Sheng Cao, Weili Han, Xiaosong Zhang, Hongfeng Chai

“…Looking ahead, the advancement of AML technologies in blockchain systems necessitates progress in several critical areas: the construction of AML datasets capable of addressing data imbalance and annotation uncertainty, development of trusted AML algorithms, design of detection mechanisms for covert financial activities, and formulation of privacy-preserving yet regulation-compliant AML solutions. …”
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GIRAFE v1: a global climate data record for precipitation accompanied by a daily sampling uncertainty by H. Konrad, R. Roca, A. Niedorf, S. Finkensieper, M. Schröder, S. Cloché, G. Panegrossi, P. Sanò, C. Kidd, C. Kidd, R. A. Jucá Oliveira, R. A. Jucá Oliveira, K. Fennig, T. Sikorski, M. Lemoine, R. Hollmann

“…GIRAFE v1 is available globally at 1° resolution as daily accumulations and monthly means for the years 2002–2022, with an implementation of continuous production planned for 2025 onwards. …”
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Deep unsupervised clustering for prostate auto-segmentation with and without hydrogel spacer by Hengrui Zhao, Biling Wang, Michael Dohopolski, Ti Bai, Steve Jiang, Dan Nguyen

“…We then used Uniform Manifold Approximation and Projection (UMAP) for dimensionality reduction and employed k-means clustering to assign each patient to a cluster. …”
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Developing and validating a machine learning-based model for predicting in-hospital mortality among ICU-admitted heart failure patients: A study utilizing the MIMIC-III database by De Su, Jie Zheng, Yue-kai Shao, Jun-ya Liu, Xin-xin Liu, Kun Yu, Bang-hai Feng, Hong Mei, Song Qin

“…Machine learning techniques offer a powerful means to identify potential risk factors and predict outcomes within multivariable clinical data. …”
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From Continent to Ocean: Investigating the Multi-Element and Precious Metal Geochemistry of the Paraná-Etendeka Large Igneous Province Using Machine Learning Tools by J. J. Lindsay, H. S. R. Hughes, C. M. Yeomans, J. C. Ø. Andersen, I. McDonald

“…Here, we use an unsupervised machine learning approach (featuring the PCA, t-SNE and k-means clustering algorithms) to investigate the geochemistry of a set of (primarily basaltic) onshore and offshore PELIP lavas. …”
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Equitable and effective clinical guidance development and dissemination: trauma aims to lead the way by Deborah M Stein, Elliott R Haut, Eileen M Bulger, Vanessa P Ho, Andres M Rubiano, Ashley Farley, Lacey N LaGrone, Danielle J Wilson, Maria Michaels, Meghan B Lane-Fall, Michael A Person, Linda Reinhart

“…The Institute of Medicine and the National Academies of Science, Engineering and Medicine have called for learning health systems, with emphasis on clinical practice guidelines (CPGs) as a means of limiting preventable deaths. Reduction in mortality has been demonstrated when evidence-based trauma CPGs are adhered to; however, guidelines are variably updated, redundant, absent, inaccessible, or perceived as irrelevant. …”
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Explaining neural networks for detection of tropical cyclones and atmospheric rivers in gridded atmospheric simulation data by T. Radke, S. Fuchs, C. Wilms, I. Polkova, I. Polkova, I. Polkova, M. Rautenhaus, M. Rautenhaus

“…<p>Detection of atmospheric features in gridded datasets from numerical simulation models is typically done by means of rule-based algorithms. Recently, the feasibility of learning feature detection tasks using supervised learning with convolutional neural networks (CNNs) has been demonstrated. …”
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DIGITAL TOOLS FOR MATCHING QUALIFICATIONS TO THE LEVELS OF THE NATIONAL QUALIFICATIONS FRAMEWORK by Volodymyr Kovtunets, Sergiy Londar, Serhii Melnyk, Oles Kovtunets

“…Therefore, some simple approximation methods for eigenvector computing may be applied using only minimal means of Microsoft Excel or analogous applications. …”
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THE AUGMENTED REALITY FUNCTIONS TO SUPPORT THE STEAM EDUCATION AT GENERAL EDUCATION INSTITUTIONS by Наталія Сороко

“…Our further research is the creation of algorithms for the use of AR for lessons and projects using the STEAM approach, which will improve the quality of education at general education institutions.…”
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Application of Hardware and Software Complex for Individualisation of Students’ Sport and Recreational Physical Activities by O. N. Moskovchenko, L. V. Zakharova, N. V. Tretyakova, N. V. Lyulina, O. A. Kattsin, G. S. Savolaynen

“…The survey sampling and processing of experimental data were carried out by means of the hardware and software complex (HSC).Results and scientific novelty. …”
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Peculiarities of application of the resources of the Moscow Electronic School platform for the formation of language competence of the students of non-linguistic specialties by Tatyana V. Masharova, Ekaterina K. Starkova, Ivan V. Shunin, Anna S. Pastukhova

“…The peculiarities of the formation of linguistic competence of students of non-linguistic specialties by means of MES include the following: the development of competence proceeds through the search and resolution of problematic situations supported by texts on special topics and posted on the platform; foreign language activities are aimed at solving tasks designed to assimilate the content of linguistic competence at algorithmic and heuristic levels; for the management of educational and speech skills of self-monitoring and self-assessment activities sets of tasks and tests that require systematic work with the resources of the database of materials are used.…”
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Disease progression & treatment need in sub-genotype C4 hepatitis B infection: a retrospective cohort study in the Northern Territory, Australia by Genevieve E. Martin, Kelly Hosking, Kelly Banz, Catherine Gargan, Geoff Stewart, Belinda Greenwood-Smith, Penelope Ramsay, Jaclyn Tate-Baker, Christine Connors, Paula Binks, Melita McKinnon, Prashanti Manchikanti, George Garambaka Gurruwiwi, Nicole Allard, Ashleigh Qama, Jessica Michaels, Emily Vintour-Cesar, Robert Batey, Catherine Marshall, Peter Nihill, Tammy-Allyn Fernandes, Karen Fuller, Steven Y. C. Tong, David Boettiger, Benjamin Cowie, Joshua S. Davis, Sarah Mariyalawuy Bukulatjpi, Jane Davies, on behalf of the Hep B PAST Partnership

“…Disease phase and cirrhotic status were determined algorithmically using clinical and laboratory data at two time points. …”
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Circadian rhythm disruption by PARP inhibitors correlates with treatment toxicity in patients with ovarian cancer and is a predictor of side effectsResearch in context by Deeksha Malhan, Janina Hesse, Nina Nelson, Kay Stankov, Jessica Nguyen, Ouda Aboumanify, Josefin Garmshausen, Gunther Rogmans, Bastian Czogalla, Jens Gerber, Martin Koch, Tomáš Kupec, Oliver Tomé, Ralf Witteler, Mustafa Deryal, Michael Eichbaum, Jalid Sehouli, Elena Ioana Braicu, Angela Relógio

“…In a subset of these patients, we performed differential gene expression and rhythmicity analysis on up to 800 genes, including clock and clock-controlled genes. Machine learning algorithms and mathematical modelling were employed to simulate patient-specific toxicity profiles and to explore correlations between gene expression patterns and treatment-related side effects. …”
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Leveraging ultrasonic-derived phenotypes and estimated breeding value to improve abdominal fat weight prediction in chickens throughout the egg laying period by Penghao Li, Zhengda Li, Fan Ying, Dan Zhu, Dawei Liu, Xianyi Song, Jie Wen, Guiping Zhao, Bingxing An

“…Abdominal fat (AF) in hens impacts egg production and may reflect poor feed efficiency, meaning that dynamic monitor of AF changes facilitate to optimize feeding management and production efficiency. …”
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Predictive analysis of clinical features for HPV status in oropharynx squamous cell carcinoma: A machine learning approach with explainability by Emily Diaz Badilla, Ignasi Cos, Claudio Sampieri, Berta Alegre, Isabel Vilaseca, Simone Balocco, Petia Radeva

“…The contribution of each variable to the prediction was substantiated by creating a 95% confidence intervals of model coefficients by means of a 10,000 sample bootstrap and by analyzing top contributors across the best-performing models. …”
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Combating Corruption in Sport: Legal Aspect (Lucha contra la corrupción en el deporte: aspecto legal) by Tetiana Kolomoiets, Maxym Tkalych, Petro Melnyk, Bogdan Panchenko, Yuliia Tolmachevska

“…Therefore, legal science has a task to determine the legal algorithms for combating sports corruption both within the country and in the international arena. …”
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Different environmental factors predict the occurrence of tick-borne encephalitis virus (TBEV) and reveal new potential risk areas across Europe via geospatial models by Patrick H. Kelly, Rob Kwark, Harrison M. Marick, Julie Davis, James H. Stark, Harish Madhava, Gerhard Dobler, Jennifer C. Moïsi

“…Region-specific ML models were defined via K-means clustering and trained according to the distribution of extracted geocoordinates relative to explanatory variables in each region. …”
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Simulación de Plataformas Robóticas de Movimiento para Aplicaciones de Realidad Virtual Mediante Filtros Digitales by Sergio Casas, Cristina Portalés, Silvia Rueda, Marcos Fernández

“…However, the set-up of the so-called washout algorithms that control the generation of self-motion is a hard process, since a great deal of tests need to be performed before reaching a proper motion fidelity. …”
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The implementation of the situational control concept of information security in automated training systems by A. M. Chernih, S. V. Fedoseev

“…It is assumed that the automated learning system is a fragment of a larger information system that contains several information paths, each of them treats different information in the protection degree from information, containing constituting state secrets, to open access information.It is considered that the technical methods, measures and means of information protection in automated learning systems implement less than half (30%) functions of subsystems of control and protection information. …”
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