Revolutionizing Histopathology: Utilizing Large Language Model for Report Interpretation and Medical Education

Authors

  • Sadia Yaseen Department of Medical Education, MedicalEducation.ORG, Lahore
  • Alishbah Saeed ENT Department, Lahore General Hospital, Lahore, Pakistan
  • Shafaq Mehmood Histopathology Department, shaikh Zayed hospital Lahore, Pakistan

DOI:

https://doi.org/10.35845/abms.2024.1.349

Abstract

The arrival of large language models like Open AI’s ChatGPT, Microsoft’s Copilot and Google’s Gemini AI heralds a revolutionary era in various medical fields including the interpretation of histopathology reports. Histopathology is a foundation in diagnostic medicine which traditionally depends on the skill of a histopathologist to interpret cytology and tissue biopsies. However, a fusion of large language models (artificial intelligence) has enhanced diagnostic accuracy and lessened the workload burden on pathologists especially in human resource-constrained setups. This editorial explores the merits and demerits of integrating large language models for interpreting histopathology reports supported by evidence.

References

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Published

2024-06-21

How to Cite

Yaseen, S., Saeed, A. . ., & Mehmood, S. (2024). Revolutionizing Histopathology: Utilizing Large Language Model for Report Interpretation and Medical Education. ADVANCES IN BASIC MEDICAL SCIENCES, 8(1), 01–02. https://doi.org/10.35845/abms.2024.1.349