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September 10, 2025Open Access

Potential Applications of Artificial Intelligence in Histopathological Diagnstics of Leukemias

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Authors

MCMieszko CzaplińskiUniversity of GdańskGRGrzegorz RedlarskiGdańsk University of TechnologyPKPaweł KowalskiGdańsk University of Technology

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Overview

This review demonstrates AI's capability to improve accuracy in leukemia diagnosis and highlights challenges of implementation.

Key Points

  • AI models achieved accuracy rates over 95% in detecting leukemias and classifying subtypes.
  • Research output on AI applications in histopathological diagnostics shows a significant increase over recent years.
  • AI can enhance diagnostic precision and reduce subjectivity in hematopathology workflows.
  • While integrating AI holds great potential, there are challenges in introducing it to routine diagnostics.

Cite This Study

Czapliński et al. (2025) studied this question.

synapsesocial.com/papers/68c1bb6354b1d3bfb60ed005https://doi.org/10.20944/preprints202508.0193.v1
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Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1An Overview of Existing Applications of Artificial Intelligence in Histopathological Diagnostics of Lymphoma: A Scoping Review2026
  2. 2Artificial Intelligence in Hematology: Diagnostic Accuracy, Implementation Challenges, and Future Directions: A Systematic Review2025 · 1 citations
  3. 3Review about Artificial Intelligence in Hematopathology; Current Uses and Future Opportunities2026
  4. 4The Role of Artificial Intelligence in the Hematology Department2025 · 4 citations
  5. 5Clinical applications of artificial intelligence in the histopathology of lymphoma: diagnosis, treatment and prognosis2025 · 2 citations