Digital Health Using Data Science

Authors

• Padmapriya Velupillai Mekandan, Marquette University
• Paramita Basak Upama, Marquette University
• Masud Rabbani, Marquette University
• Amity Ali, Marquette University
• Sheikh Iqbal Ahamed, Marquette UniversityFollow

Document Type

Conference Proceeding

Publication Date

2025

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Source Publication

IEEE 49th Annual Computers, Software, and Applications Conference (COMPSAC)

Source ISSN

2836-3795

Original Item ID

DOI: 10.1109/COMPSAC65507.2025.00330

Abstract

The digitization of healthcare has led to an unprecedented growth in health-related data, offering new opportunities to transform clinical decision-making, disease prediction, and patient engagement. However, extracting actionable insights from diverse data sources such as electronic health records, wearable devices, and mobile health apps requires a fusion of domain knowledge in healthcare and technical expertise in data science. This paper presents a structured, interdisciplinary framework for digital health that emphasizes practical strategies for data acquisition, preprocessing, feature engineering, machine learning, and ethical data use. The model promotes a holistic understanding of digital health challenges and opportunities, preparing future professionals to apply computational tools in real-world healthcare environments responsibly.

Comments

Accepted version. Published as part of the proceedings of the IEEE 49th Annual Computers, Software, and Applications Conference (COMPSAC), 2025: 2344-2351. DOI. ©2025 IEEE. Used with permission.

Recommended Citation

Mekandan, Padmapriya Velupillai; Upama, Paramita Basak; Rabbani, Masud; Ali, Amity; and Ahamed, Sheikh Iqbal, "Digital Health Using Data Science" (2025). Computer Science Faculty Research and Publications. 123.
https://epublications.marquette.edu/comp_fac/123