Vol. 1 No. 2 (2021): Human-Computer Interaction Perspectives
Articles

Precision Health Informatics - Big Data and AI for Personalized Healthcare Solutions: Analyzing Their Roles in Generating Insights and Facilitating Personalized Healthcare Solutions

Mohan Raparthi
Independent Researcher
Bhavani Prasad Kasaraneni
Independent Researcher, USA
Krishna Kanth Kondapaka
Independent Researcher, CA ,USA
Swaroop Reddy Gayam
Independent Researcher and Senior Software Engineer at TJMax, USA
Praveen Thuniki
Independent Research, Sr Program Analyst, Georgia, USA
Siva Sarana Kuna
Independent Researcher and Software Developer, USA
Venkata Siva Prakash Nimmagadda
Independent Researcher, USA
Sudharshan Putha
Independent Researcher and Senior Software Developer, USA
Sandeep Pushyamitra Pattyam
Independent Researcher and Data Engineer, USA
Mohit Kumar Sahu
Independent Researcher and Senior Software Engineer, CA, USA
Cover

Published 15-07-2021

Keywords

  • Precision health informatics,
  • big data,
  • artificial intelligence,
  • personalized healthcare,
  • machine learning,
  • deep learning,
  • clinical decision-making,
  • data privacy,
  • bias,
  • interpretability
  • ...More
    Less

How to Cite

[1]
M. Raparthi, “Precision Health Informatics - Big Data and AI for Personalized Healthcare Solutions: Analyzing Their Roles in Generating Insights and Facilitating Personalized Healthcare Solutions”, Human-Computer Interaction Persp., vol. 1, no. 2, pp. 1–8, Jul. 2021.

Abstract

Precision health informatics is revolutionizing healthcare by leveraging big data and artificial intelligence (AI) to deliver personalized healthcare solutions. This paper explores the intersection of big data and AI in precision health informatics, examining their roles in generating insights and facilitating personalized healthcare. We discuss how big data, with its vast and varied sources, provides a rich resource for understanding health and disease at individual and population levels. AI, particularly machine learning and deep learning algorithms, enables the extraction of meaningful patterns and predictions from this data, aiding in clinical decision-making and treatment planning.

The paper also highlights the challenges and ethical considerations in the use of big data and AI in precision health informatics, including data privacy, bias in algorithms, and the need for interpretability. Furthermore, we explore the future prospects of this field, including the integration of genomics, wearable sensors, and other emerging technologies, and their potential to further personalize healthcare. Overall, this paper provides insights into how the integration of big data and AI is transforming healthcare delivery, leading to more precise, effective, and personalized healthcare solutions.

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