Zobrazeno 1 - 10
of 107
pro vyhledávání: '"RF: random forest"'
Publikováno v:
IEEE Access, Vol 11, Pp 26441-26458 (2023)
Standard inspections of buildings are not always possible because of human flaws in prediction. Hence, we need more stable, scalable, and efficient automated processes. Structure Health Monitoring (SHM) is one of the automation systems for forecastin
Externí odkaz:
https://doaj.org/article/4527b477dcb54c878330fda02f58bfc8
Akademický článek
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Autor:
Mazarire, Theresa Taona, Ratshiedana, Phathutshedzo Eugene, Nyamugama, Adolph, Adam, Elhadi, Chirima, George
Publikováno v:
South African Journal of Geomatics; Vol. 9 No. 2 (2020); 333-347
Accurate and detailed studies in crop mapping are crucial in precision agriculture, yield estimations, and crop monitoring. This study focused on exploring the utility of Sentinel-2 data in mapping of crop types and testing the two machine learning a
Publikováno v:
Computational and Structural Biotechnology Journal, Vol 19, Iss, Pp 2833-2850 (2021)
Computational and Structural Biotechnology Journal
Computational and Structural Biotechnology Journal
Graphical abstract
The worldwide health crisis caused by the SARS-Cov-2 virus has resulted in>3 million deaths so far. Improving early screening, diagnosis and prognosis of the disease are critical steps in assisting healthcare professionals to
The worldwide health crisis caused by the SARS-Cov-2 virus has resulted in>3 million deaths so far. Improving early screening, diagnosis and prognosis of the disease are critical steps in assisting healthcare professionals to
Autor:
Victor Maojo, Nereida Rodriguez-Fernandez, Adrian Carballal, Carlos Fernandez-Lozano, Francisco J. Novoa, Alejandro Pazos, Paula Carracedo-Reboredo, Francisco Cedrón, Jose Liñares-Blanco
Publikováno v:
Computational and Structural Biotechnology Journal, Vol 19, Iss, Pp 4538-4558 (2021)
RUC. Repositorio da Universidade da Coruña
instname
Computational and Structural Biotechnology Journal
RUC. Repositorio da Universidade da Coruña
instname
Computational and Structural Biotechnology Journal
Graphical abstract
Highlights • Machine Learning in drug discovery has greatly benefited the pharmaceutical industry. • Application of machine algorithms must entail a robust design in real clinical tasks. • Trending machine learning algor
Highlights • Machine Learning in drug discovery has greatly benefited the pharmaceutical industry. • Application of machine algorithms must entail a robust design in real clinical tasks. • Trending machine learning algor
Autor:
Mr. Madhu H. K, Dr. D. Ramesh
In the present pandemic situation, health care data is generated voluminously in an unstructured format posing challenge to technology in perspective of analysis, classification and prediction. The data generated is converted to structured format. Su
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od______2659::a14f952eab72a2abd5d76e11ec438e9f
https://zenodo.org/record/8090684
https://zenodo.org/record/8090684
Akademický článek
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Autor:
Marie A. Chaix, James Ellis, Cedric Manlhiot, Emily Lam, Paul C. Nathan, Neha Parmar, Anne Christie, Jane Lougheed, Paul F. Kantor, Guoliang Meng, Luc Mertens, Anastasia Miron, Leonard S. Sender, Stacey Marjerrison, Shayna Zelcer, Ashok Kumar Manickaraj, David C. Hodgson, Rejane Dillenburg, Seema Mital, Oyediran Akinrinade, Herschel Rosenberg, Roderick Yao, Caroline Kinnear, Myriam Lafreniere-Roula, Mylene Bassal
Publikováno v:
Paediatrics Publications
JACC: CardioOncology
JACC: CardioOncology
Background Despite known clinical risk factors, predicting anthracycline cardiotoxicity remains challenging. Objectives This study sought to develop a clinical and genetic risk prediction model for anthracycline cardiotoxicity in childhood cancer sur
Publikováno v:
Computational and Structural Biotechnology Journal, Vol 18, Iss, Pp 834-842 (2020)
Computational and Structural Biotechnology Journal
Computational and Structural Biotechnology Journal
Circular RNA (circRNA) plays an important role in the development of diseases, and it provides a novel idea for drug development. Accurate identification of circRNAs is important for a deeper understanding of their functions. In this study, we develo