Search Results - research algorithm

Modeling Asteroseismic Yields for the Roman Galactic Bulge Time-domain Survey by Trevor J. Weiss, Noah J. Downing, Marc H. Pinsonneault, Joel C. Zinn, Dennis Stello, Timothy R. Bedding, Kaili Cao, Marc Hon, Claudia Reyes, B. Scott Gaudi, Robert F. Wilson, Daniel Huber, Sanjib Sharma

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ANALISIS PROSES BERPIKIR KOMPUTASI SISWA PADA MATERI BARISAN ARITMETIKA BERDASARKAN KECERDASAN MAJEMUK by Rosevita Melati, Toto Nusantara, Mochammad Hafiizh

“…This study aims to describe the process of computational thinking in arithmetic sequences based on multiple intelligences. This research is a qualitative descriptive study. Participants in this study were selected using purposive sampling techniques based on students' multiple intelligences. …”
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Machine Learning and Interpretability Study for Predicting 30-Day Unplanned Readmission Risk of Schizophrenia: A Retrospective Study by Tan Y, Chen G, Wang S, Zhan X, Cheng R, Qiao L, Zhang Z, Liu Y

“…The model was constructed using five ML algorithms: logistic regression (LR), decision tree (DT), random forest (RF), support vector machine (SVM), and extreme gradient boosting (XGB). …”
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Construction and Validation of a Machine Learning-Based Risk Prediction Model for Sleep Quality in Patients with OSA by Tong Y, Wen K, Li E, Ai F, Tang P, Wen H, Guo B

“…This study not only deepens understanding of the factors affecting sleep quality in OSA patients, but also provides a powerful predictive tool for clinical doctors. Future research can explore the potential of incorporating these predictive factors into comprehensive treatment strategies to improve patient prognosis and overall quality of life.Keywords: machine learning, risk prediction, sleep quality, OSA, SHAP…”
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Integrated Bioinformatics and Experimental Validation Reveal Macrophage Polarization-Related Biomarkers for Osteoarthritis Diagnosis by He Q, Liu L, Hu X, Lin L, Song Z, Xia Y, Lin Q, Wei J, Li S

“…Least absolute shrinkage and selection operator (LASSO), random forest (RF), and support vector machine recursive feature elimination (SVM-RFE) algorithms were used to identify hub genes and construct a diagnostic model validated through internal datasets and multiple external bulk RNA-seq and single-cell RNA-seq data. …”
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Methodology of Determining the Location of the Distribution Center of Material Flows in a Combined Scheme of Goods Delivery by Svetlana A. Zhestkova

“…Introduction. The research is aimed at developing a methodology for determining the optimal location of material flows’ distribution center, taking into account the formation of ring routes based on the use of the fictitious nodes and branches’ method (FNB), in order to minimize overall logistical costs. …”
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Predicting biomass transportation costs: A machine learning approach for enhanced biofuel competitiveness by Ali Omidkar, Razieh Es’haghian, Hua Song

“…Consequently, this study explores the predictive capabilities of two alternative machine learning algorithms: random forests and artificial neural networks. …”
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Development and validation of a machine-learning-based model for identification of genes associated with sepsis-associated acute kidney injury by Chen Lin, Meng Zheng, Wensi Wu, Zhishan Wang, Guofeng Lu, Shaodan Feng, Xinlan Zhang

“…We assessed 113 combinations of 12 different algorithms to develop an internally and externally validated machine-learning model for diagnosing AKI. …”
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Exploring the Potential Regulatory Mechanisms of Mitophagy in Ischemic Cardiomyopathy by Li Z, Kong J, Xi S, Jin Z, Yang F, Zhu Z, Liu L

“…Then, biomarkers were identified through machine learning algorithms and Receiver Operating Characteristic curve (ROC) analysis. …”
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Energy-Aware and Reliability-Based Localization-Free Cooperative Acoustic Wireless Sensor Networks by Junaid Qadir, Ubaid Ullah, Beatriz Sainz-De-Abajo, Begona Garcia Zapirain, Goncalo Marques, Isabel de la Torre Diez

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A review of altimetry waveform retracking for inland water levels by Xinyuan Deng, Linghong Ke, Liguang Jiang, Karina Nielsen, Xiaomei Fan, Jida Wang, Chunqiao Song

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Artificial Intelligence in Pediatric Orthopedics: A Comprehensive Review by Andrea Vescio, Gianluca Testa, Marco Sapienza, Filippo Familiari, Michele Mercurio, Giorgio Gasparini, Sergio de Salvatore, Fabrizio Donati, Federico Canavese, Vito Pavone

“…For developmental dysplasia of the hip, deep learning algorithms demonstrated high diagnostic performance in radiographic interpretation. …”
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First M87 Event Horizon Telescope Results. VI. The Shadow and Mass of the Central Black Hole by The Event Horizon Telescope Collaboration, Kazunori Akiyama, Antxon Alberdi, Walter Alef, Keiichi Asada, Rebecca Azulay, Anne-Kathrin Baczko, David Ball, Mislav Baloković, John Barrett, Dan Bintley, Lindy Blackburn, Wilfred Boland, Katherine L. Bouman, Geoffrey C. Bower, Michael Bremer, Christiaan D. Brinkerink, Roger Brissenden, Silke Britzen, Avery E. Broderick, Dominique Broguiere, Thomas Bronzwaer, Do-Young Byun, John E. Carlstrom, Andrew Chael, Chi-kwan Chan, Shami Chatterjee, Koushik Chatterjee, Ming-Tang Chen, Yongjun Chen, Ilje Cho, Pierre Christian, John E. Conway, James M. Cordes, Geoffrey B. Crew, Yuzhu Cui, Jordy Davelaar, Mariafelicia De Laurentis, Roger Deane, Jessica Dempsey, Gregory Desvignes, Jason Dexter, Sheperd S. Doeleman, Ralph P. Eatough, Heino Falcke, Vincent L. Fish, Ed Fomalont, Raquel Fraga-Encinas, Per Friberg, Christian M. Fromm, José L. Gómez, Peter Galison, Charles F. Gammie, Roberto García, Olivier Gentaz, Boris Georgiev, Ciriaco Goddi, Roman Gold, Minfeng Gu, Mark Gurwell, Kazuhiro Hada, Michael H. Hecht, Ronald Hesper, Luis C. Ho, Paul Ho, Mareki Honma, Chih-Wei L. Huang, Lei Huang, David H. Hughes, Shiro Ikeda, Makoto Inoue, Sara Issaoun, David J. James, Buell T. Jannuzi, Michael Janssen, Britton Jeter, Wu Jiang, Michael D. Johnson, Svetlana Jorstad, Taehyun Jung, Mansour Karami, Ramesh Karuppusamy, Tomohisa Kawashima, Garrett K. Keating, Mark Kettenis, Jae-Young Kim, Junhan Kim, Jongsoo Kim, Motoki Kino, Jun Yi Koay, Patrick M. Koch, Shoko Koyama, Michael Kramer, Carsten Kramer, Thomas P. Krichbaum, Cheng-Yu Kuo, Tod R. Lauer, Sang-Sung Lee, Yan-Rong Li, Zhiyuan Li, Michael Lindqvist, Kuo Liu, Elisabetta Liuzzo, Wen-Ping Lo, Andrei P. Lobanov, Laurent Loinard, Colin Lonsdale, Ru-Sen Lu, Nicholas R. MacDonald, Jirong Mao, Sera Markoff, Daniel P. Marrone, Alan P. Marscher, Iván Martí-Vidal, Satoki Matsushita, Lynn D. Matthews, Lia Medeiros, Karl M. Menten, Yosuke Mizuno, Izumi Mizuno, James M. Moran, Kotaro Moriyama, Monika Moscibrodzka, Cornelia Müller, Hiroshi Nagai, Neil M. Nagar, Masanori Nakamura, Ramesh Narayan, Gopal Narayanan, Iniyan Natarajan, Roberto Neri, Chunchong Ni, Aristeidis Noutsos, Hiroki Okino, Héctor Olivares, Tomoaki Oyama, Feryal Özel, Daniel C. M. Palumbo, Nimesh Patel, Ue-Li Pen, Dominic W. Pesce, Vincent Piétu, Richard Plambeck, Aleksandar PopStefanija, Oliver Porth, Ben Prather, Jorge A. Preciado-López, Dimitrios Psaltis, Hung-Yi Pu, Venkatessh Ramakrishnan, Ramprasad Rao, Mark G. Rawlings, Alexander W. Raymond, Luciano Rezzolla, Bart Ripperda, Freek Roelofs, Alan Rogers, Eduardo Ros, Mel Rose, Arash Roshanineshat, Helge Rottmann, Alan L. Roy, Chet Ruszczyk, Benjamin R. Ryan, Kazi L. J. Rygl, Salvador Sánchez, David Sánchez-Arguelles, Mahito Sasada, Tuomas Savolainen, F. Peter Schloerb, Karl-Friedrich Schuster, Lijing Shao, Zhiqiang Shen, Des Small, Bong Won Sohn, Jason SooHoo, Fumie Tazaki, Paul Tiede, Remo P. J. Tilanus, Michael Titus, Kenji Toma, Pablo Torne, Tyler Trent, Sascha Trippe, Shuichiro Tsuda, Ilse van Bemmel, Huib Jan van Langevelde, Daniel R. van Rossum, Jan Wagner, John Wardle, Jonathan Weintroub, Norbert Wex, Robert Wharton, Maciek Wielgus, George N. Wong, Qingwen Wu, André Young, Ken Young, Ziri Younsi, Feng Yuan, Ye-Fei Yuan, J. Anton Zensus, Guangyao Zhao, Shan-Shan Zhao, Ziyan Zhu, Joseph R. Farah, Zheng Meyer-Zhao, Daniel Michalik, Andrew Nadolski, Hiroaki Nishioka, Nicolas Pradel, Rurik A. Primiani, Kamal Souccar, Laura Vertatschitsch, Paul Yamaguchi

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Artificial intelligence demonstrates potential to enhance orthopaedic imaging across multiple modalities: A systematic review by Umile Giuseppe Longo, Alberto Lalli, Guido Nicodemi, Matteo Giuseppe Pisani, Alessandro De Sire, Pieter D'Hooghe, Ara Nazarian, Jacob F. Oeding, Balint Zsidai, Kristian Samuelsson

“…However, the current body of literature lacks comprehensive statistical analysis and randomized controlled trials, underscoring the need for further research to validate these findings in clinical settings. …”
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Oxidative balance score predicts chronic kidney disease risk in overweight adults: a NHANES-based machine learning study by Leying Zhao, Leying Zhao, Cong Zhao, Cong Zhao, Yuchen Fu, Yuchen Fu, Xiaochang Wu, Xiaochang Wu, Xuezhe Wang, Xuezhe Wang, Yaoxian Wang, Yaoxian Wang, Yaoxian Wang, Huijuan Zheng

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Obstructive sleep apnea severity and pathophysiological traits in overlap syndrome: Insights from the SNOOzzzE cohort by Janna Raphelson, Ana Sanchez‐Azofra, Jeremy E. Orr, Gabriela Parra, Lana McGinnis, Alexis Salinas, Steven Luu, Scott A. Sands, Ali Azarbarzin, Robert L. Owens, Jose M. Marin, Atul Malhotra, Christopher N. Schmickl

“…OSA severity and mechanisms differ in OVS versus OSA‐only. Future research should seek to evaluate these differences for their prognostic ability.…”
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Predicting Early-Onset Colorectal Cancer in Individuals Below Screening Age Using Machine Learning and Real-World Data: Case Control Study by Chengkun Sun, Erin Mobley, Michael Quillen, Max Parker, Meghan Daly, Rui Wang, Isabela Visintin, Ziad Awad, Jennifer Fishe, Alexander Parker, Thomas George, Jiang Bian, Jie Xu

“…MethodsWe identified a cohort of patients under the age of 45 years from the OneFlorida+ Clinical Research Consortium. Given the distinct pathology of colon cancer (CC) and rectal cancer (RC), we created separate prediction models for each cancer type with various ML algorithms. …”
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Atrial fibrillation and chronic kidney disease: main clinical characteristics of patients in selected subjects of the Russian Federation by M. A. Druzhilov, T. Yu. Kuznetsova, O. Yu. Druzhilova, U. D. Arustamova, D. V. Gavrilov, A. V. Gusev

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An Explainable Machine Learning Approach for IoT-Supported Shaft Power Estimation and Performance Analysis for Marine Vessels by Yiannis Kiouvrekis, Katerina Gkirtzou, Sotiris Zikas, Dimitris Kalatzis, Theodor Panagiotakopoulos, Zoran Lajic, Dimitris Papathanasiou, Ioannis Filippopoulos

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External reference pricing for medicines in Ukraine: latest trends by L. I. Kucherenko, I. V. Nizhenkovska, N. V. Sholoiko, L. O. Hala, N. O. Datsiuk

“…Different approaches, including different reference countries and price calculation algorithms, are applied for the price regulation of medicines in NEML and the “Affordable Medicines” program. …”
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