Barque, Barry MalickRodrigues, Pedro JoãoPaula Filho, Pedro Luiz dePeixoto, Raquel SilvaLeite, Deborah Catharine de Assis2024-10-092024-10-092024Barque, Barry Malick; Rodrigues, Pedro João Soares; Paula Filho, Pedro Luiz de; Peixoto, Raquel Silva; Leite, Deborah Catharine de Assis (2024). Prediction of Health of Corals Mussismilia hispida Based on the Microorganisms Present in their Microbiome. In 3rd International Conference on Optimization, Learning Algorithms and Applications (OL2A 2023). Cham: Springer Nature, Vol. 1, p. 409–423. ISBN 978-3-031-53024-1978-3-031-53024-1978-3-031-53025-8http://hdl.handle.net/10198/30390One of the most diverse and productive marine ecosystems in the world are the corals, providing not only tourism but also an important economic contribution to the countries that have them on their coasts. Thanks to genome sequencing techniques, it is possible to identify the microorganisms that form the coral microbiome. The generation of large amounts of data, thanks to the low cost of sequencing since 2005, provides an opening for the use of artificial neural networks for the advancement of sciences such as biology and medicine. This work aims to predict the healthy microbiome present in samples of Mussismilia hispida coral, using machine learning algorithms, in which the algorithms SVM, Decision Tree, and Random Forest achieved a rate of 61%, 74%, and 72%, respectively. Additionally, it aims to identify possible microorganisms related to the disease in question in corals.engCoral reefMicrobiomeMachine learning algorithmconference object10.1007/978-3-031-53025-8_28