Applications of Machine Learning Algorithms in Health Data Science (HDS) for Next Research Directions: A Survey Report

Year : 2024 | Volume : 11 | Issue : 01 | Page : –

    Vinay Bhatt

  1. Mayank Kumar

  1. Research Scholar, Department of Computer Science and Engineering Asian International University, Imphal West, Manipur, India
  2. Associate Professor, Department Of Computer Science And Engineering Asian International University, Imphal West, Manipur, India


In present time, data science is in big trend under computer science. The functioning of this technology is purely based on other advance technology known as machine learning (ML). Data science and machine learning are subsets of artificial intelligence (AI). When a process of data science is used in healthcare systems, the new system is known as health data science (HDS). HDS is a branch of data science used for handle the large amount of data in healthcare system. Recently, data science is used for handle and analysis the large volume of data (structured or unstructured) with accuracy by using the different techniques with algorithms of machine learning. This survey paper presented the ML applications in data science using different previous research. In this paper, firstly discuss on the introduction of paper with related information, secondly, discuss on review of literature on behalf of previous research, thirdly, discuss on machine learning with its techniques and examples, fourthly, discuss on stages of data science, fifthly, discuss on weakness or research gaps of previous research works according to literature review and finally discuss on proposed work for next research directions using observations to research gaps.

Keywords: AI, ML, Data science, Health Data Science, Supervised Learning, Unsupervised Learning, Reinforcement Learning, Deep Learning, Deep-Reinforcement Learning, ANN

[This article belongs to Journal of Artificial Intelligence Research & Advances(joaira)]

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Regular Issue Subscription Review Article
Volume 11
Issue 01
Received December 29, 2023
Accepted January 4, 2024
Published January 17, 2024