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International Journal of Creative and Open Research in Engineering and Management

A Peer-Reviewed, Open-Access International Journal Supporting Multidisciplinary Research, Digital Publishing Standards, DOI Registration, and Academic Indexing.
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ISSN: 3108-1754 (Online)
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ISO Certification: 9001:2015
Publication Fee: 599/- INR
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License: CC BY 4.0
Peer Review: Double Blind
Volume 02, Issue 8

Published on: August 2026

INTEGRATION OF ARTIFICIAL INTELLIGENCE AND DIGITAL MORPHOLOGY IN HAEMATOLOGY LABORATORIES: A COMPREHENSIVE REVIEW FOR CLINICAL PRACTICE AND FUTURE HORIZONS

Nasib Ali Seleibam Monojit Sen Rabina Bariam Sanda Jingieid Kharngi Md. Noor Habib

Dr. Amirul Hassan Barbhuiya

Department of Medical Laboratory Technology

University of Science and technology of Meghalaya, Ri-Bhoi, Meghalaya793101

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Plagiarism Passed Peer Reviewed Open Access

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Abstract

The morphological evaluation of blood and bone‐marrow smears remains an essential component of Haematology diagnostics despite the significant growth of automated Haematology analyser s. The advent of digital slide imaging (digital morphology) and artificial intelligence (AI) driven image analysis offers a transformative opportunity to increase efficiency, consistency, and diagnostic precision in Haematology laboratories. This review provides a detailed examination of the evolution of Haematology diagnostics, current AI methodologies in cell classification, slide digitisation technologies, real‐world clinical applications, validation and regulatory considerations, and future directions including the role of AI in personalised medicine. The evidence demonstrates notable benefits improved turnaround times, enhanced accuracy, remote review capability but also underscores critical challenges: slide quality dependence, algorithmic limitations with rare and abnormal cells, data standardisation, validation and regulatory frameworks. For laboratories seeking to adopt AI‐integrated digital morphology, a hybrid human‐AI workflow with robust validation and ongoing performance monitoring is currently the most pragmatic route. Emerging trends such as foundation models, multimodal integration and federated learning suggest that the future Haematology laboratory may be highly digital, adaptive and personalised yet human expertise remains indispensable.

How to Cite this Paper

Ali, N., Sen, S. M., Bariam, R., Kharngi, S. J. & Habib, M. N. (2026). Integration of Artificial Intelligence and Digital Morphology in Haematology Laboratories: A Comprehensive Review for Clinical Practice and Future Horizons. International Journal of Creative and Open Research in Engineering and Management, <i>02</i>(8), 1-9. https://doi.org/10.55041/ijcope.v2i8.004

Ali, Nasib, et al.. "Integration of Artificial Intelligence and Digital Morphology in Haematology Laboratories: A Comprehensive Review for Clinical Practice and Future Horizons." International Journal of Creative and Open Research in Engineering and Management, vol. 02, no. 8, 2026, pp. 1-9. doi:https://doi.org/10.55041/ijcope.v2i8.004.

Ali, Nasib,Seleibam Sen,Rabina Bariam,Sanda Kharngi, and Md. Habib. "Integration of Artificial Intelligence and Digital Morphology in Haematology Laboratories: A Comprehensive Review for Clinical Practice and Future Horizons." International Journal of Creative and Open Research in Engineering and Management 02, no. 8 (2026): 1-9. https://doi.org/https://doi.org/10.55041/ijcope.v2i8.004.

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References


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  • Published on: Aug 05 2026
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