An Overview on Disease Prediction for Preventive Care of Health Deterioration

Machine learning in health care has recently made headlines. With the wide spread increase of population, the need for reliable mechanism to prevent diseases has increased in manifold. In the recent days there is an increase in health problems in majority of the population across the globe. The reas...

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Bibliographic Details
Published inInternational journal of engineering and advanced technology Vol. 8; no. 5s; pp. 255 - 261
Main Authors N, Mohan Kumar K, Sampath, S., Imran, Mohammed
Format Journal Article
LanguageEnglish
Published 29.06.2019
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Summary:Machine learning in health care has recently made headlines. With the wide spread increase of population, the need for reliable mechanism to prevent diseases has increased in manifold. In the recent days there is an increase in health problems in majority of the population across the globe. The reason for health problems is not specific but it has become very uncertain. If we take a sample from the population, it should not be a surprise to see a person suffering from ailments irrespective of age and quality of life. For example chronicle diseases are found in people at a very young age. So this situation poses a serious challenge for clinical experts to find the root cause. It is difficult to accurately predict the future health based on the current health status because the scenario might not be same for all the patients. Providing an affordable, high quality health care service has become a big challenge. In this regard, preventive care of diseases is investigated for decades. It is an area of regular extension of research works and progression day by day and there is sufficient literature available on prediction of diseases. Our work includes a disciplined study to consolidate existing works on prediction and classification of diseases. This paper will provide technical insight and paves way for future developments in the health care field.
ISSN:2249-8958
2249-8958
DOI:10.35940/ijeat.E1051.0585S19