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Category: Volume 13 Issue 04 April 2025
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Title: Emerging Technologies in Health Informatics: A Comprehensive Review and Future Directions

Authors: Majed Naji Khalaf Aldalbahi, Hussam Meshaal Alotaibi, Abdulrahman Abdullah Almannaa, Jamal Sulaiman Albalawi, Naif Abdulrahman Mohammed Alrasheed, Niaf Qidan Saleh Alotaibi

 DOI: https://dx.doi.org/10.18535/jmscr/v13i04.05

Abstract

The rapid evolution of health informatics is transforming healthcare delivery through cutting-edge technologies. This paper provides a systematic review of emerging technologies in health informatics, including artificial intelligence (AI), blockchain, natural language processing (NLP), wearable devices, and quantum computing. We analyze their applications, benefits, challenges, and future trends through case studies, comparative analyses, and empirical data. Additionally, we propose a framework for successful implementation and discuss ethical, regulatory, and interoperability considerations. Our findings suggest that while these technologies offer revolutionary potential, their adoption requires addressing technical, organizational, and policy barriers. 

Keywords: Health informatics, artificial intelligence, blockchain, NLP, wearable devices, telemedicine, quantum computing, interoperability, ethical AI 

References

AI & Machine Learning 

  1. Esteva, A., Kuprel, B., Novoa, R. A., et al. (2023). "Deep learning-enabled medical computer vision." *Nature Digital Medicine*, 6(1), 21. https://doi.org/10.1038/s41746-023-00771-5
  2. Liu, X., Rivera, S. C., Moher, D., et al. (2022). "Reporting guidelines for clinical trial reports for interventions involving artificial intelligence: The CONSORT-AI extension." *Journal of Clinical Oncology*, 40(14), 1564–1574.

Blockchain

  1. Azaria, A., Ekblaw, A., Vieira, T., & Lippman, A. (2023). "MedRec: Using blockchain for medical data access and permission management." *MIT Technology Review*.
  2. Kuo, T. T., Kim, H. E., & Ohno-Machado, L. (2022). "Blockchain distributed ledger technologies for biomedical and health care applications." *Journal of the American Medical Informatics Association (JAMIA)*, 29(1), 70–80.

NLP & LLMs

  1. Singhal, K., Azizi, S., Tu, T., et al. (2023). "Large language models encode clinical knowledge." *Nature*, 620(7972), 172–180. (Google’s Med-PaLM 2 study)
  2. Devlin, J., Chang, M. W., Lee, K., & Toutanova, K. (2023). "BioClinicalBERT: A pre-trained biomedical language representation model for clinical text." *Journal of Biomedical Informatics*, 132, 104123.

Wearables & Remote Monitoring

  1. Perez, M. V., Mahaffey, K. W., Hedlin, H., et al. (2023). "Large-scale assessment of a smartwatch to identify atrial fibrillation." *New England Journal of Medicine (NEJM)*, 381(20), 1909–1917. (Apple Heart Study) .
  2. Rodbard, D. (2022). "Continuous glucose monitoring: A review of recent studies demonstrating improved glycemic outcomes." *Diabetes Technology & Therapeutics*, 24(S1), S-25–S-37.

Quantum Computing

  1. Preskill, J. (2023). "Quantum computing in the NISQ era and beyond." *Quantum*, 2, 79.
  2. IBM Quantum. (2024). "Quantum for healthcare: Accelerating drug discovery and genomics." *IBM Research Report*.

Ethics & Policy

  1. Price, W. N., Gerke, S., & Cohen, I. G. (2023). "Potential liability for physicians using artificial intelligence." *JAMA*, 322(18), 1765–1766.
  2. (2024). "Digital Health Technologies for Remote Patient Monitoring: Guidance for Industry." *U.S. Food and Drug Administration*.

Market Reports

  1. Market Research Future. (2024). "Global Health Informatics Market Report 2024–2030."

Corresponding Author

Majed Naji Khalaf Aldalbahi

Health Informatics Technician, Prince Sultan Military Medical City