ItemConference Paper

A Comprehensive Review of Advanced Analytics for Predicting HRQoL in Cancer Survivors Using a Synergistic Approach

Title
A Comprehensive Review of Advanced Analytics for Predicting HRQoL in Cancer Survivors Using a Synergistic Approach
Creator
Kale, Vaishnaw Gorakhnath; Kshirsagar, Pravin Ramdas; Unhelkar, Bhuvan; Chakrabarti, Prasun; Upreti, Kamal; Jain, Rituraj
Description
This systematic review explores the role applied and emerging methods including AI, Explainable AI and Quantum machine learning techniques in the prediction of Health-Related Quality of Life (HRQoL) of cancer survivors. It also gives possible benefits and limitation of using the advanced analytics to predict the HRQoL. In all, 141 research papers implemented in the last fifteen years with focus between the years 2008 to 2023 are analyzed. For the convenience, this literature review is divided into four primary categories - (i) Artificial intelligence, (ii) Explainable artificial intelligence, (iii) Quantum machine learning, and (iv) Synergistic integration. The third way the present systematic review paper differs from other papers in the domain is that the paper offers a direction of future research. Furthermore, the hypothetical illustration is provided in order to compare outcomes of the synergistic approach with the existing data. Consequently, this analysis provides beneficial insights for further research and development of the synergistic approach in both research and clinical practice. The assessment shows that there is a continued need for research focusing on improving the quality of life of those that survived cancer. 2025 IEEE.
Source
2025 International Conference on Intelligent Control, Computing and Communications, IC3 2025;pp.1345-1350
Date
01-01-2025
Publisher
Institute of Electrical and Electronics Engineers Inc.
Subject
Artificial Intelligence; Cancer Survivorship; Explainable AI; Quantum Machine Learning
Coverage
Kale V.G., School of Computer Science Engineering and Applications, D. Y. Patil International University, MS, Pune, India; Kshirsagar P.R., J.D College of Engg & Mgmt., Department of Electronics Engineering, MS, Nagpur, India; Unhelkar B., Muma College of Business, University of South Florida, (Sarasota-Manatee Campus), United States; Chakrabarti P., Sir Padampat Singhania University, Department of Computer Science & Engineering, Rajasthan, Udaipur, India; Upreti K., Christ University, Department of Computer Science, Delhi NCR, Ghaziabad, India; Jain R., Marwadi University, Department of Information Technology, Gujarat, Rajkot, India
Rights
Restricted Access; Hardcopy may be available in the library
Relation
ISBN: 979-833152749-5;
Format
online
Language
English
Type
Conference paper

Citation

Kale, Vaishnaw Gorakhnath; Kshirsagar, Pravin Ramdas; Unhelkar, Bhuvan; Chakrabarti, Prasun; Upreti, Kamal; Jain, Rituraj, “A Comprehensive Review of Advanced Analytics for Predicting HRQoL in Cancer Survivors Using a Synergistic Approach,” CHRIST (Deemed To Be University) Institutional Repository, accessed June 17, 2026, https://archives.christuniversity.in/items/show/25868.

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