Open Access

REVIEW

Data-Driven Healthcare: The Role of Computational Methods in Medical Innovation

by Hariharasakthisudhan Ponnarengan^1,*, Sivakumar Rajendran², Vikas Khalkar³, Gunapriya Devarajan⁴, Logesh Kamaraj⁵

1 Department of Mechanical Engineering, Dr. Mahalingam College of Engineering and Technology, Pollachi, Coimbatore, Tamil Nadu, 642003, India
2 Department of Mechanical Engineering, JKKN College of Engineering and Technology, Kumarapalayam, Namakkal, Tamil Nadu, 637209, India
3 Department of Mechanical Engineering, Gharda Institute of Technology, Lavel, Maharashtra, 415708, India
4 Department of Electrical and Electronics Engineering, Sri Eshwar College of Engineering, Coimbatore, Tamilnadu, 641202, India
5 Department of Mechanical Engineering, Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology, Chennai, 600062, India

* Corresponding Author: Hariharasakthisudhan Ponnarengan. Email:

Computer Modeling in Engineering & Sciences 2025, 142(1), 1-48. https://doi.org/10.32604/cmes.2024.056605

Received 26 July 2024; Accepted 17 October 2024; Issue published 17 December 2024

Abstract

The purpose of this review is to explore the intersection of computational engineering and biomedical science, highlighting the transformative potential this convergence holds for innovation in healthcare and medical research. The review covers key topics such as computational modelling, bioinformatics, machine learning in medical diagnostics, and the integration of wearable technology for real-time health monitoring. Major findings indicate that computational models have significantly enhanced the understanding of complex biological systems, while machine learning algorithms have improved the accuracy of disease prediction and diagnosis. The synergy between bioinformatics and computational techniques has led to breakthroughs in personalized medicine, enabling more precise treatment strategies. Additionally, the integration of wearable devices with advanced computational methods has opened new avenues for continuous health monitoring and early disease detection. The review emphasizes the need for interdisciplinary collaboration to further advance this field. Future research should focus on developing more robust and scalable computational models, enhancing data integration techniques, and addressing ethical considerations related to data privacy and security. By fostering innovation at the intersection of these disciplines, the potential to revolutionize healthcare delivery and outcomes becomes increasingly attainable.

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Keywords

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