Advanced Computer Network for Healthcare Sector – Liver Function Diagnosis

Janardhana, Kedri and Rajasekar, P. and Shali, A. and Vijayaragavan, M. and David, D. Stalin (2021) Advanced Computer Network for Healthcare Sector – Liver Function Diagnosis. In: I3CAC 2021, 7-8 June 2021, Bharath University, Chennai, India.

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Abstract

Innovation technology has been implemented in different field, especially in life science, for example, genome sequencing, hereditary printing, proteomic and metabolomic examination, electronic clinical records, and patient-revealed wellbeing information have delivered a wide scope of information, from an assortment of people, cell types, and problems (huge information). Notwithstanding, this information should be incorporated and dissected in the event that it is to deliver models or ideas about physiological working or pathogenesis components. The majority of this information is freely accessible, which permits specialists anyplace to look for side effects of explicit biologic cycles or helpful targets for explicit infections or sorts of patients. We are evaluating ongoing advances in the field of computational and foundational science, and featuring the prospects of analysts utilizing enormous informational collections in the fields of gastroenterology and hepatology, to supplement conventional techniques for demonstrative and restorative access. We present and look at two AI calculations, which naturally create choice trees from research facility information. TheBayesNet classifier gives that the highest accuracy level which is 82.68%, and the highest precision value is 79.94% which is produced by NaivebayesMultinomial algorithm. This system recommends that the BayesNet classifier and N

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: classifier big data precision accuracy algorithm recall
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
QA75 Electronic computers. Computer science
Depositing User: EAI Editor IV
Date Deposited: 11 Jun 2021 08:01
Last Modified: 11 Jun 2021 08:01
URI: https://eprints.eudl.eu/id/eprint/3839

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