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1. Azuaje, F., Artificial intelligence for precision oncology: beyond patient stratification. NPJ Precis. Oncol., 3, 6, 2019, https://doi.org/10.1038/s41698-019-0078-1.

2. Bauer, H., Patel, M., Veira, J., The Internet of Things: sizing up the opportunity, McKinsey & Company, New York (NY), 2016, Available from: http://www.mckinsey.com/industries/high-tech/our-insights/the-internet-of-things-sizing-up-the-opportunity.

3. Baloch, Z., Shaikh, F., Unar, M., A context-aware data fusion approach for health-IoT. Int. J. Inf. Technol., 10, 241–245, 2018, 10. 10.1007/s41870-018-0116-1.

4. Choi, H., A Risk Stratification Model for Lung Cancer Based on Gene Coexpression Network and Deep Learning. Applications of Bioinformatics and Systems Biology in Precision Medicine and Immuno Oncology, Research Article | Open Access, BioMed Research International, 2018, 2914280, 11, 2018. 2018 |Article ID 2914280, 11 pages, 2018, https://doi.org/10.1155/2018/2914280, Received 13 Oct 2017| Revised 07 Dec 2017 | Accepted 11 Dec 2017 |Published 16 Jan.\.

5. Deen, M.J., Information and communications technologies for elderly ubiquitous healthcare in a smart home. Pers. Ubiquitous Comput., 19, 573–599, 2015.

6. Gao, W. et al., Fully integrated wearable sensor arrays for multiplexed in situ perspiration analysis. Nature, 529, 7587, 509–514, 2016.

7. Gyllensten, I.C. et al., A novel wearable vest for tracking pulmonary congestion in acutely decompensated heart failure. Int. J. Cardiol., 177, 1, 199–201, 2014.

8. Haghighat, M., Abdel-Mottaleb, M., Alhalabi, W., Discriminant correlation analysis: real-time feature level fusion for multimodal biometric recognition. IEEE Trans. Inf. Forensics Secur., 11, 9, 1984–96, 2016.

9. Kadir, T. and Gleeson, F., Lung cancer prediction using machine learning and advanced imaging techniques. Transl. Lung Cancer Res., 7, 3, 304–312, 2018, Retrieved from http://tlcr.amegroups.com/article/view/21998.

10. Kumar, S. and Maninder, S., Big data analytics for healthcare industry: impact, applications, and tools. Big Data Min. Anal., 2, 48–57, 2019, 10.26599/BDMA.2018.9020031.

11. Li, Y., Ge, D., Gu, J. et al., A large cohort study identifying a novel prognosis prediction model for lung adenocarcinoma through machine learning strategies. BMC Cancer, 19, 886, 2019, https://doi.org/10.1186/s12885-019-6101-7.

12. Li, Y., Wu, et al., Wiki-Health: A Big Data Platform for Health Sensor Data Management. in: Cloud Computing Applications for Quality Healthcare Delivery, A. Moumtzoglou, A. Kastania (Ed.), pp. 59–77, IGI Global, 2014, 10.4018/978-1-4666-6118-9.ch004, 2014.

13. Lisa, A. and Gustafson, D.H., The Role of Technology in Healthcare Innovation. A Commentary. J. Dual Diagn. Author manuscript; available PMC 2014 Jan 1. 2013, 9, 1, 101–103, 2013, J Dual Diagn. Published online 2012 Nov 27.

14. Macedo, F. et al., Computer-aided detection (CADe) and diagnosis (CADx) system for lung cancer with likelihood of malignancy. Biomed. Eng. Online, 2, 15, 2016.

15. Mike, Hoover, W., Strome, T., Kanwal, S., Transforming healthcare through big data strategies for leveraging big data in the healthcare industry, Health IT Outcomes, USA, 2013, http://ihealthtran.com/iHT2 BigData 2013.pdf.

16. Rastogi, R., Chaturvedi, D.K., Satya, S., Arora, N., Trivedi, P., Gupta, M., Singhal, P., Gulati, M., MM Big Data Applications: Statistical Resultant Analysis of Psychosomatic Survey on Various Human Personality Indicators, ICICI 2018 Paper as Book Chapter, Chapter 25, © Springer Nature Singapore Pte Ltd, Singapore, 2020, Book Subtitle: Proceedings of Second International Conference on Computational Intelligence, 2018, https://doi.org/10.1007/978-981-13-8222-2_25.

17. Singh, Y. and Chauhan, A.S., Neural Networks in Data Mining. J. Theor. Appl. Inf. Technol., 5, 6, 37–42, 14, 2005.

18. Sun, and Reddy, C.K., Big data analytics for healthcare, in: Proc. 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 1525–1525, 2013.

19. Wu, M. and Luo, J., Wearable technology applications in healthcare: A literature review. Online. J. Nurs. Inform. (OJNI), 23, 3, 1, Fall. 2019, Available at http://www.himss.org/ojn.

20. Xu, J., Yang, P., Xue, S. et al., Translating cancer genomics into precision medicine with artificial intelligence: applications, challenges and future perspectives. Hum. Genet., 138, 109–124, https://doi.org/10.1007/s00439-019-01970-5, 2019.

21. Zanella, A., Bui, N., Castellani, A., Vangelista, L., Zorzi, M., Internet of things for smart cities. IEEE Internet Things J., 1, 1, 22–32, 2014.

22. Zhao, W. and Wang, H., Strategic decision-making learning from label distributions: an approach for facial age estimation. Sensors, 16, 994–1013, 2016.

*Corresponding author: rohit.rastogi@abes.ac.in