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ARTIFICIAL INTELLIGENCE-DRIVEN FACE RECOGNITION IN HEALTHCARE INFORMATICS: A SYSTEMATIC REVIEW OF TECHNOLOGIES, CLINICAL APPLICATIONS, PRIVACY CHALLENGES, AND FUTURE RESEARCH DIRECTIONS

AUTHORS:
Md Bahar Ali Mollah
Tathagata Roy Chowdhury
Mentor
Affiliation
Department of Computer Science and Engineering, Elitte College of Engineering, Kolkata, West Bengal, India
DOI: 10.55041/ijsmt.v2i7.007
CC BY 4.0 License:
This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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Abstract
Artificial Intelligence (AI)-driven face recognition has emerged as a transformative technology in healthcare informatics, offering secure, contactless, and efficient solutions for patient identification, authentication, clinical monitoring, and healthcare service delivery. Recent advances in deep learning and computer vision have significantly improved the accuracy and robustness of facial recognition systems, enabling their integration into smart hospitals, telemedicine platforms, and intelligent healthcare management systems. At the same time, developments in cognitive face perception research have provided deeper insights into facial identity recognition, facial motion analysis, gender perception, and memory mechanisms, which are fundamental to designing reliable recognition systems. This systematic review synthesizes current research on AI-driven face recognition in healthcare informatics by examining technological developments, clinical applications, cognitive foundations, and emerging healthcare challenges. The reviewed literature also highlights the growing role of AI in disease diagnosis, breast cancer screening, patient-centered healthcare, and healthcare quality improvement, demonstrating the broader impact of intelligent technologies within modern healthcare environments. Furthermore, this review discusses important concerns related to privacy protection, ethical deployment, data security, fairness, and real-world implementation challenges that continue to influence the adoption of facial recognition technologies in clinical practice. Based on the analyzed studies, this paper presents a structured taxonomy of existing approaches, identifies key research gaps, and proposes future research directions for developing trustworthy, explainable, and privacy-aware AI-driven face recognition systems capable of supporting next-generation healthcare informatics and intelligent clinical decision-making.
Keywords
Artificial Intelligence; Face Recognition; Healthcare Informatics; Deep Learning; Computer Vision; Privacy-Preserving Healthcare.
Article Information
PUBLICATION DETAILS
Review Type:
Double-Blind Peer Review
License:
CC BY-NC 4.0
Volume/Issue:
Volume 02, Issue 7
Review Rounds:
2
Article Type:
Research Article
Publication Date:
Jul 07 2026
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Mollah, M. B. A. & Chowdhury, T. R. (2026). Artificial Intelligence-Driven Face Recognition in Healthcare Informatics: A Systematic Review of Technologies, Clinical Applications, Privacy Challenges, and Future Research Directions. International Journal of Science, Strategic Management and Technology, 02(7). https://doi.org/10.55041/ijsmt.v2i7.007

Mollah, Md, and Tathagata Chowdhury. "Artificial Intelligence-Driven Face Recognition in Healthcare Informatics: A Systematic Review of Technologies, Clinical Applications, Privacy Challenges, and Future Research Directions." International Journal of Science, Strategic Management and Technology, vol. 02, no. 7, 2026, pp. . doi:https://doi.org/10.55041/ijsmt.v2i7.007.

Mollah, Md, and Tathagata Chowdhury. "Artificial Intelligence-Driven Face Recognition in Healthcare Informatics: A Systematic Review of Technologies, Clinical Applications, Privacy Challenges, and Future Research Directions." International Journal of Science, Strategic Management and Technology 02, no. 7 (2026). https://doi.org/https://doi.org/10.55041/ijsmt.v2i7.007.

References
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[9] B. D. Gupta, N. Das, S. Das, and S. Roy, "SmartVote India: A Secure Digital Election Platform," International Journal of Science, Strategic Management and Technology, vol. 2, no. 6, 2026, doi: 10.55041/ijsmt.v2i6.038.

 

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Ethics and Compliance
✓ All ethical standards met
This article has undergone plagiarism screening and double-blind peer review. Editorial policies have been followed. Authors retain copyright under CC BY-NC 4.0 license. The research complies with ethical standards and institutional guidelines.
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