Precision medicine is the future of the Healthcare system, which is going to change the generalized medicine prescription. To establish precision medicine in the place of generalized medicine, new frameworks have to be designed that will utilize the existing enormous volumes of data. Big data is the term that represents massive volumes of data being generated through various means, including in Healthcare. In this work, a new framework for precision medicine is proposed beginning from big data, applying Classification techniques to avail reduced data and there on to achieve precision medicine with an intelligent medicine advisor. In the first phase, we evaluated the noisy big data with innovative hierarchical decision attention networks, Multi class classification using Map Reduce mechanism. This phase is experimented with a diabetes dataset. This output can be utilized by the next phase component called Intelligent Medicine advisor to get system recommended precision medicine, which can help the medical practitioner to join the Artificial Intelligence in their treatment.
CITATION STYLE
Sobhanbabu, B., & Bharati, K. F. (2023). An Intelligent Evolutionary Schema on Precision Medicine for Diabetes Using Big Data Analytics. Revue d’Intelligence Artificielle, 37(2), 433–439. https://doi.org/10.18280/ria.370220
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