Application of Supervised Machine Learning to Recognize Competent Level and Mixed Antinuclear Antibody Patterns Based on ICAP International Consensus

Application of Supervised Machine Learning to Recognize Competent Level and Mixed Antinuclear Antibody Patterns Based on ICAP International Consensus

Background: Antinuclear antibody pattern recognition is vital for autoimmune disease diagnosis but labor-intensive for manual interpretation. To develop an automated pattern recognition system, we established machine learning models based on the International Consensus on Antinuclear Antibody Patter...

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Bibliographic Details
Main Authors: Yi-Da Wu, Ruey-Kai Sheu, Chih-Wei Chung, Yen-Ching Wu, Chiao-Chi Ou, Chien-Wen Hsiao, Huang-Chen Chang, Ying-Chieh Huang, Yi-Ming Chen, Win-Tsung Lo, Lun-Chi Chen, Chien-Chung Huang, Tsu-Yi Hsieh, Wen-Nan Huang, Tsai-Hung Yen, Yun-Wen Chen, Chia-Yu Chen, Yi-Hsing Chen
Format: Article
Language:English
Published: MDPI AG 2021-04-01
Series:Diagnostics
Subjects:
Hep-2 cell
ICAP
artificial intelligence
antinuclear antibody
machine learning
Online Access:https://www.mdpi.com/2075-4418/11/4/642

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https://www.mdpi.com/2075-4418/11/4/642

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