Measurement Uncertainty Evaluation of a Leukemia Recognition Algorithm Based on Patient Clinical Data

JIANG Chaofan; YAN Jingting; WANG Tingting; ZHANG Jiatao; CUI Weiqun

doi:10.12338/j.issn.2096-9015.2024.0125

Volume 68 Issue 7

Jul. 2024

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Article Navigation > Metrology Science and Technology > 2024 > 68(7): 72-77

JIANG Chaofan, YAN Jingting, WANG Tingting, ZHANG Jiatao, CUI Weiqun. Measurement Uncertainty Evaluation of a Leukemia Recognition Algorithm Based on Patient Clinical Data[J]. Metrology Science and Technology, 2024, 68(7): 72-77. doi: 10.12338/j.issn.2096-9015.2024.0125

Citation:

JIANG Chaofan, YAN Jingting, WANG Tingting, ZHANG Jiatao, CUI Weiqun. Measurement Uncertainty Evaluation of a Leukemia Recognition Algorithm Based on Patient Clinical Data[J]. Metrology Science and Technology, 2024, 68(7): 72-77. doi: 10.12338/j.issn.2096-9015.2024.0125

Citation:

JIANG Chaofan, YAN Jingting, WANG Tingting, ZHANG Jiatao, CUI Weiqun. Measurement Uncertainty Evaluation of a Leukemia Recognition Algorithm Based on Patient Clinical Data[J]. Metrology Science and Technology, 2024, 68(7): 72-77. doi: 10.12338/j.issn.2096-9015.2024.0125

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Measurement Uncertainty Evaluation of a Leukemia Recognition Algorithm Based on Patient Clinical Data

doi: 10.12338/j.issn.2096-9015.2024.0125

National Institute of Metrology, Beijing 100029, China

Received Date: 2024-04-15
Accepted Date: 2024-05-08
Rev Recd Date: 2024-05-09

Available Online: 2024-06-18

Publish Date: 2024-07-30

Abstract

Abstract

With the advent of the digital age, algorithms increasingly dominate the development of various industries and the emergence of new sectors, giving rise to a digital economy-led industrial landscape. Metrology, as the science of measurement and its application, is rapidly entering the digital era, with the promotion of digital transformation in the metrology industry becoming a top priority. Consequently, evaluating the accuracy and reliability of algorithmic software outputs has become a focal point of current research. This paper employs a digital metrology method based on reference data, using the output of a leukemia recognition algorithm software applied to patient clinical test data as the measurement result. It establishes an evaluation model for the leukemia recognition algorithm, outlines the specific process for assessing measurement uncertainty, and calculates the combined standard uncertainty of the measurand.
- metrology,
- digital transformation,
- reference data,
- digital metrology,
- algorithm software,
- algorithm uncertainty

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References(28)

References

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