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Diagnostic agreement between ChatGPT-based interpretation of laboratory-generated flow cytometry graphical outputs and hematologist consensus in suspected acute leukemia

Truvace record
TRV-2026-2874raw data (JSON)
Version
v1Published
First published
Evidence type
Observational study
Sources
1 sourcePeer-reviewed
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84df196f62ba…check it

Accurate, rapid, and standardized interpretation of multiparametric flow cytometry findings is essential for clinical decision-making in patients evaluated for suspected acute leukemia. This study aimed to evaluate the diagnostic performance of ChatGPT, a general-purpose large language model, in interpreting de-identified, laboratory-generated flow cytometry graphical outputs from patients with suspected acute leukemia and to assess its agreement with the consensus interpretation of two hematologists in terms of…

58Gain side

How the two sides scoreClose call

54Problem side

The gain

In a retrospective study of 560 patients with suspected acute leukemia, ChatGPT (GPT-5.5) reading flow cytometry plots matched hematologist consensus diagnoses with 78.8% accuracy and substantial agreement (kappa 0.712).

The problem

In a retrospective study of 560 suspected acute leukemia cases, ChatGPT (GPT-5.5) overestimated blast percentage by a mean 3.92 points and differed systematically from hematologists on AML (p = 0.008), T-ALL (p = 0.023) and no-pathology cases (p = 0.041).

A fixed formula sets both scores from the evidence and its sources. Reader votes don’t move them.

What the scores mean

G is the gain side, out of 100. It goes up when the gain is specific, when it measurably helped people and when the sources behind it are strong.

P is the problem side, out of 100. It goes up when the problem is specific, when it measurably hurt people and when the sources behind it are strong.

What this doesn’t fix

Expert hematologist validation remains essential, particularly for AML and T-ALL classification, blast percentage estimation and hematogone discrimination, where ChatGPT differed systematically from experts or overestimated blasts.

Sources

1 on file
  1. Cytometry Part B: Clinical Cytometrydoi:10.1002/cyto.b.70097
    Peer-reviewed2026-11-11

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v1

Truvace Impact Record TRV-2026-2874, v1: “Diagnostic agreement between ChatGPT-based interpretation of laboratory-generated flow cytometry graphical outputs and hematologist consensus in suspected acute leukemia.” Truvace, 2026-11-13. /record/TRV-2026-2874 (accessed on the day you copy it). sha256 84df196f62ba2a24…

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