Please use this identifier to cite or link to this item: http://ir.lib.seu.ac.lk/handle/123456789/6357
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dc.contributor.authorAkmal Jahan, M. A. C.-
dc.contributor.authorJumani, S. F.-
dc.date.accessioned2022-12-08T06:43:34Z-
dc.date.available2022-12-08T06:43:34Z-
dc.date.issued2022-11-15-
dc.identifier.citation11th Annual Science Research Sessions 2022 (ASRS-2022) Proceedings on "“Scientific Engagement for Sustainable Futuristic Innovations”. 15th November 2022. Faculty of Applied Sciences, South Eastern University of Sri Lanka, Sammanthurai, Sri Lanka. pp. 26.en_US
dc.identifier.isbn978-624-5736-60-7-
dc.identifier.urihttp://ir.lib.seu.ac.lk/handle/123456789/6357-
dc.description.abstractMicrobiome acts pervasive roles in different environments. Microbiomes have a huge impact on human health and wealth. The human microbiome resides on and inside the human body. It carries out beneficial advantages in the human body such as metabolism, digestion of foods and regulates immune systems, etc. Likewise, an imbalance of the measure count of the microbiome causes symptoms of diseases. Earlier prediction and identification of diseases and taking precautions may help to reduce the loss of living beings and prevent the high risk of contagious diseases. The study of microbiome genetics leads to help in disease prediction. Microbiome data provides different features to predict diseases. Machine learning algorithms are used to predict diseases based on microbiome data. Machine learning algorithms are user-friendly methods to predict diseases. They provide fast outputs at a cheaper cost and help to predict future opportunities as well. To get the best algorithm for the prediction, we need to extensively search and experimentally select it. This work evaluates the impact of a set of machine learning algorithms for the prediction of disease using microbiome data.en_US
dc.language.isoen_USen_US
dc.subjectMicrobiomeen_US
dc.subjectMachine Learning Algorithmsen_US
dc.subjectDisease Predictionen_US
dc.titleImpact of machine learning algorithms on disease prediction using microbiome dataen_US
dc.typeArticleen_US
Appears in Collections:11th Annual Science Research Session - FAS

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