Comparison of cardiovascular risk prediction models developed using machine learning based on data from a Sri Lankan cohort with World Health Organization risk charts for predictin... by Anuradhani Kasturiratne, Hithanadura Janaka de Silva, Chamila Mettananda, Anuradha Supun Dassanayake, Norihiro Kato, Rajitha Wickremasinghe, Maheeka Solangaarachchige, Prasanna Haddela

“…The ML models were derived using classification algorithms of the supervised learning technique. We compared the predictive performance of our ML models with WHO risk charts (2019, Southeast Asia) using area under the receiver operating characteristic curves (AUC-ROC) and calibration plots. …”
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Ensamblaje automático de piezas con desviaciones dimensionales by Javier Gámez García, Alejandro Sánchez García, Silvia Satorres Martínez, Juan Gómez Ortega

“…In particular, different approaches were studied: surface measurement sensors for transparent and deformable objects, actuation systems that could modify the assembly position of the parts, and control algorithms that could carry out this adaptive assembly automatically. …”
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Cross-sectional and longitudinal genotype to phenotype surveillance of SARS-CoV-2 variants over the first four years of the COVID-19 pandemicResearch in context by Anouschka Akerman, Christina Fichter, Vanessa Milogiannakis, Camille Esneau, Mariana Ruiz Silva, Tim Ison, Joseph A. Lopez, Zin Naing, Joanna Caguicla, Supavadee Amatayakul-Chantler, Nathan Roth, Sandro Manni, Thomas Hauser, Thomas Barnes, Tino Boss, Anna Condylios, Malinna Yeang, Kenta Sato, Nathan N. Bartlett, David Darley, Gail Matthews, Damien J. Stark, Susan Promsri, William D. Rawlinson, Benjamin Murrell, Anthony D. Kelleher, Dominic Dwyer, Vitali Sintchenko, Jen Kok, Sally Ellis, Kelsi Marris, Elizabeth Knight, Veronic C. Hoad, David O. Irving, Iain Gosbell, Fabienne Brilot, James Wood, Anupriya Aggarwal, Stuart G. Turville

“…We monitored emerging variants through viral culture, growth algorithms, neutralisation responses and changing entry requirements defined by ACE2 and TMPRSS2 receptor use. …”
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Improving accessibility to radiotherapy services in Cali, Colombia: cross-sectional equity analyses using open data and big data travel times from 2020 by Luis Gabriel Cuervo, Carmen Juliana Villamizar, Daniel Cuervo, Pablo Zapata, Maria B. Ospina, Sara Marcela Valencia, Alfredo Polo, Ángela Suárez, Maria O. Bula, J. Jaime Miranda, Gynna Millan, Diana Elizabeth Cuervo, Nancy J. Owens, Felipe Piquero, Janet Hatcher-Roberts, Gabriel Dario Paredes, María Fernanda Navarro, Ingrid Liliana Minotta, Carmen Palta, Eliana Martínez-Herrera, Ciro Jaramillo, on behalf of the AMORE Project Collaboration

“…The platform integrates open data, including the location of radiotherapy services, the disaggregated sociodemographic microdata for the population and places of residence, and big data for travel times from Google Distance Matrix API. We used genetic algorithms to identify optimal locations for new services. …”
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Sepsis-Associated Acute Kidney Disease Incidence, Trajectory, and Outcomes by Hsiu-Yin Chiang, Chih-Chia Liang, Ya-Luan Hsiao, Uyen-Minh Le, Yi-Ching Chang, Pei-Shan Chen, David Ray Chang, I-Wen Ting, Hung-Chieh Yeh, Chin-Chi Kuo

“…This study aimed to use data algorithms on the electronic health records to trace the SA-AKD trajectory from acute kidney injury (AKI) to chronic kidney disease (CKD). …”
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Aerosol layer height (ALH) retrievals from oxygen absorption bands: intercomparison and validation among different satellite platforms, GEMS, EPIC, and TROPOMI by H. Kim, H. Kim, X. Chen, X. Chen, J. Wang, J. Wang, J. Wang, J. Wang, Z. Lu, Z. Lu, Z. Lu, M. Zhou, G. R. Carmichael, G. R. Carmichael, S. S. Park, J. Kim

“…The differences due to the inconsistent definitions of ALH in various retrieval algorithms are investigated and eliminated before comparison. …”
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Autoconcepto físico en estudiantes universitarios: Generación de perfiles por clasificación jerárquica sobre componentes principales (Physical self-concept in university students:... by Luis Alberto Cardozo, Jhonatan C. Peña-Ibagón, Widad Florez-Escobar, Carlos A. Castillo-Daza, Diego A. Bonilla-Ocampo, Javier L. Reina-Monroy

“…The aims of this study were i) to analyze and compare the physical self-concept in university students considering possible differences between sexes and associations with socioeconomic status and age, and ii) to generate student profiles using unsupervised machine learning algorithms. A total of 230 Colombian students between 18 and 38 years of age from the Physical Education (n = 118) and Psychology (n = 112) majors participated in this cross-sectional study. …”
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Development and validation of a screening tool for sepsis without laboratory results in the emergency department: a machine learning studyResearch in context by Shan Jiang, Shuai Dai, Yulin Li, Xianlong Zhou, Cheng Jiang, Cong Tian, Yana Yuan, Chengwei Li, Yan Zhao

“…The qSepsis was derived by three ML algorithms, including logistic regression (LR), random forest (RF), and extreme gradient boosting (XGB). …”
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Research Status and Prospects of Key Technologies for Rice Smart Unmanned Farms by YU Fenghua, XU Tongyu, GUO Zhonghui, BAI Juchi, XIANG Shuang, GUO Sien, JIN Zhongyu, LI Shilong, WANG Shikuan, LIU Meihan, HUI Yinxuan

“…Rice yield estimation technology is mainly used to predict yield by combining multi-source data and algorithms, but there are still problems such as the difficulty of integrating multi-source data, which requires further research. …”
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Navigating Ethical Dilemmas Of Generative AI In Medical Writing by Qurrat Ulain Hamdan, Waleed Umar, Mahnoor Hasan

“…Generative AI in Medical Writing Generative AI tools or “chatbots” combine the adaptive learning capabilities of deep learning algorithms and natural language processing, resulting in a virtual assistant or aide that is capable of answering queries, following commands, and improving its responses according to the vast data available on the Internet in addition to user responses.3 This has allowed the accomplishment of various complex tasks within seconds that would otherwise require hours of trial and error. …”
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MSH-YOLOv8: Mushroom Small Object Detection Method with Scale Reconstruction and Fusion by YE Dapeng, JING Jun, ZHANG Zhide, LI Huihuang, WU Haoyu, XIE Limin

“…[Objective]Traditional object detection algorithms applied in the agricultural field, such as those used for crop growth monitoring and harvesting, often suffer from insufficient accuracy. …”
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Un outil éthique, automatisé et totalement autonome pour étudier la cognition chez les primates by Jonas Fizet, Adam Rimele, Thierry Pebayle, Jean Christophe Cassel, Christian Kelche, Helene Meunier

“…Une particularité du programme que nous avons développé est l’implémentation d’un nouveau processus d’apprentissage totalement informatisé et autonome, ne nécessitant aucune intervention de l’expérimentateur tout au long de l’étude. Basé sur des algorithmes intelligents, ce dernier permet une variation en temps réel de la difficulté des tâches en fonction de l’évolution des performances individuelles. …”
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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 general, the use of blockchain can affect the following: Risk: Blockchain minimizes the possibility of changing and falsifying information by using strong encryption and security algorithms. Also, by using distributed technology, the reliability of data access and visibility increases. …”
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Estimation and evaluation of iron reserves in the eastern area of Eileh1 mine, Razavi Khorasan province by Hamid Esmati Daroneh, Maryam Gholamzadeh

“…Introduction The evaluation of mineral reserves is conducted using various methods, which differ in calculation algorithms, accuracy, speed, the state of the mineral, and the characteristics of exploration activities (Madani, 1997; Ahmadi, 2010). …”
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Development and Evaluation of an AI-based Exergame Training System for Ice-Hockey Players: a Randomized Controlled Trial by Nicole Sieber, Simon Walser, Thomas Weber, Raphael Gubler, Hannes Badertscher, Patrick Eggenberger

“…., machine learning) was applied to train and validate algorithms to accurately detect joint positions of the human body based on large open-source training and validation data sets. …”
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