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Original Article
Intelligent Healthcare Tracking System Using Predictive Analytics
Ajeet Pandit1
Jayant Ghormode2
Bhagyashree Kumbhare3
Yamini Laxane4
1 2 Students, MCA, Smt. Radhikatai Pandav College of Engineering, Nagpur, Maharashtra, India. 3 HOD & Professor, MCA, Smt. Radhikatai Pandav College of Engineering, Nagpur, Maharashtra, India. 4 Professor, MCA, Smt. Radhikatai Pandav College of Engineering, Nagpur, Maharashtra, India.
Published Online: May-August 2026
Pages: 276-282
Cite this article
↗ https://www.doi.org/10.59256/indjcst.20260502032
References
1. S. Ramanathan and P. Krishnamurthy, "Continuous vital sign monitoring for early detection of clinical deterioration in general ward patients,"
Journal of Hospital Medicine, vol. 18, no. 4, pp. 312-328, 2022.
2. M. Patel, R. Desai, and N. Shah, "Machine learning models for predicting sepsis onset using electronic health record data," International
Journal of Medical Informatics, vol. 157, no. 2, pp. 104-119, 2023.
3. T. Nakamura and K. Watanabe, and H. Mori, "Portable heart monitoring patches for detecting irregular heartbeats outside hospital settings,"
IEEE Journal of Biomedical and Health Informatics, vol. 27, no. 2, pp. 890-905, 2023.
4. L. Fernandez, C. O'Brien, and J. Mallick, "Explainable artificial intelligence for clinical decision support," Artificial Intelligence in Medicine,
vol. 124, no. 1, pp. 78-94, 2023.
5. A. Gupta and S. Reddy, "Alarm fatigue in intensive care units causes consequences and countermeasures," Critical Care Nursing Clinics,
vol. 34, no. 3, pp. 245-261, 2022.
6. K. Yamamoto, Y. Tanaka, R. Suzuki, and M. Kobayashi, "Decentralized machine learning approaches for collaborative healthcare data
analysis while preserving patient privacy," Journal of the American Medical Informatics Association, vol. 30, no. 4, pp. 712-728, 2023.
7. P. Singh, A. Kaur, and V. Sharma, "Edge computing architectures for real time patient monitoring in home healthcare settings," IEEE Internet
of Things Journal, vol. 9, no. 14, pp. 12560-12575, 2022.
8. R. Mehrotra and S. Chakraborty, "Predictive analytics for early warning of heart failure exacerbation using wearable derived activity
patterns," Circulation Digital Health Journal, vol. 5, no. 2, pp. 88-103, 2023.
9. D. Wilson and E. Thompson, "Regulatory pathways for machine learning based medical devices lessons from recent FDA approvals," Journal
of Law and Biosciences, vol. 10, no. 1, pp. 45-67, 2023.
10. B. Kumar, S. Prasad, and S. Verma, R. Pillai, and A. Nair, "Economic value and return on investment for continuous remote patient tracking
in vulnerable populations a comprehensive review," Health Economics Review, vol. 13, no. 1, pp. 55-72, 2023.
Journal of Hospital Medicine, vol. 18, no. 4, pp. 312-328, 2022.
2. M. Patel, R. Desai, and N. Shah, "Machine learning models for predicting sepsis onset using electronic health record data," International
Journal of Medical Informatics, vol. 157, no. 2, pp. 104-119, 2023.
3. T. Nakamura and K. Watanabe, and H. Mori, "Portable heart monitoring patches for detecting irregular heartbeats outside hospital settings,"
IEEE Journal of Biomedical and Health Informatics, vol. 27, no. 2, pp. 890-905, 2023.
4. L. Fernandez, C. O'Brien, and J. Mallick, "Explainable artificial intelligence for clinical decision support," Artificial Intelligence in Medicine,
vol. 124, no. 1, pp. 78-94, 2023.
5. A. Gupta and S. Reddy, "Alarm fatigue in intensive care units causes consequences and countermeasures," Critical Care Nursing Clinics,
vol. 34, no. 3, pp. 245-261, 2022.
6. K. Yamamoto, Y. Tanaka, R. Suzuki, and M. Kobayashi, "Decentralized machine learning approaches for collaborative healthcare data
analysis while preserving patient privacy," Journal of the American Medical Informatics Association, vol. 30, no. 4, pp. 712-728, 2023.
7. P. Singh, A. Kaur, and V. Sharma, "Edge computing architectures for real time patient monitoring in home healthcare settings," IEEE Internet
of Things Journal, vol. 9, no. 14, pp. 12560-12575, 2022.
8. R. Mehrotra and S. Chakraborty, "Predictive analytics for early warning of heart failure exacerbation using wearable derived activity
patterns," Circulation Digital Health Journal, vol. 5, no. 2, pp. 88-103, 2023.
9. D. Wilson and E. Thompson, "Regulatory pathways for machine learning based medical devices lessons from recent FDA approvals," Journal
of Law and Biosciences, vol. 10, no. 1, pp. 45-67, 2023.
10. B. Kumar, S. Prasad, and S. Verma, R. Pillai, and A. Nair, "Economic value and return on investment for continuous remote patient tracking
in vulnerable populations a comprehensive review," Health Economics Review, vol. 13, no. 1, pp. 55-72, 2023.
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