Open AccessAdvancement in Precision Medicine and Recommendation System for Clinical Trials Using Deep Learning Methods
Author(s) -
A.P. Ponselvakumar,
S. Anandamurugan,
K. Logeswaran,
S. Nivashini,
S.K. Showentharya,
S. Swetha Jayashree
Publication year - 2021
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/1055/1/012110
Subject(s) - precision medicine , personalized medicine , deep learning , health care , computer science , big data , personalized learning , artificial intelligence , quality (philosophy) , data science , focus (optics) , healthcare system , medicine , bioinformatics , data mining , psychology , teaching method , pedagogy , philosophy , open learning , economic growth , pathology , optics , biology , epistemology , physics , economics , cooperative learning
The arena for precision medicine has made vast development in progress with big data, deep learning. The personalized health information provides more insight on patient care in all directions which gives better treatment. Many researchers and peoples accept personalized provides more quality of diagnosis and medicine. This paper provides an overview various methods, algorithms, frameworks developed for personalized healthcare. In this article focus on two main accept one is recommendation system for personalized healthcare which provides more data insight mechanism and approach to diagnosis a patient, second it focus deep learning mechanisms in various fields of healthcare, bioinformatics and genomics to deliver accurate results based on advancements in algorithm. This article reveals both combination of recommendation system along with deep learning quality of precision healthcare achieved to patients.