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PREDICTIVE ANALYTICS FOR BREAST CANCER SUSCEPTIBILITY AND PROGNOSIS

Ravindran, Krishna Prasaad (2019) PREDICTIVE ANALYTICS FOR BREAST CANCER SUSCEPTIBILITY AND PROGNOSIS. IRC, Universiti Teknologi PETRONAS. (Submitted)

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Abstract

A good healthcare system is important to progression or growth of a country. Healthcare has proven to be a large influencing factor towards the economy of a country. Only if the citizen of a country is healthy then a certain productivity rate can be achieved. This is because there will be less financial burden and much reliable workforce. In today’s modern world with technological advancement, healthcare industry has essentially become one of the most important sectors in most developing countries. Management system in healthcare industry also need to adapt with the technology that are available in the market. Many healthcare sectors are still lagging in terms of merging the use of technology into improving their services. What if there is a way to predict the future outcome in terms of illness risk that is most likely to occur. It would make life easier for caregivers to prepare upfront to provide the best service to the health patients. Ergo, the development of a prediction model using machine learning is made to classify and predict the breast cancer susceptibility to provide better prognosis and determine the risk based on the tumor condition.

Item Type: Final Year Project
Academic Subject : Academic Department - Information Communication Technology
Subject: Q Science > Q Science (General)
Divisions: Sciences and Information Technology > Computer and Information Sciences
Depositing User: Ahmad Suhairi Mohamed Lazim
Date Deposited: 09 Sep 2021 19:59
Last Modified: 09 Sep 2021 19:59
URI: http://utpedia.utp.edu.my/id/eprint/20907

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