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Artificial intelligence to differentiate asthma from COPD in medico-administrative databases by Hassan Joumaa; Raphaël Sigogne; Milka Maravic; Lucas Perray; Arnaud Bourdin; Nicolas Roche is a Medicine article available to read on EtoBox.

What is Artificial intelligence to differentiate asthma from COPD in medico-administrative databases about?

## Abstract ## Introduction Discriminating asthma from chronic obstructive pulmonary disease (COPD) using medico-administrative databases is challenging but necessary for medico-economic analyses focusing on respiratory diseases. Artificial intelligence (AI) may improve dedicated algorithms. ## Objectives To assess performance of different AI-based approaches to distinguish asthmatics from COPD patients in medico-administrative databases where the clinical diagnosis is absent. An “Asthma COPD Overlap” category was defined to further test whether AI can detect complexity. ## Methods This study included 178,962 patients treated by two “R03” treatment prescriptions at least from January 2016 to December 2018 and managed by either a general practitioner and/or a pulmonologist participating in a permanent longitudinal observatory of prescription in ambulatory medicine (LPD). Clinical diagnoses are available in this database and were used as gold standards to develop diagnostic rules. Three types of AI approaches were explored using data restricted to demographics and treatment dispensations: multinomial regression, gradient boosting and recurrent neural networks (RNN). The best performi

Who reads Artificial intelligence to differentiate asthma from COPD in medico-administrative databases?

Author

Hassan Joumaa; Raphaël Sigogne; Milka Maravic; Lucas Perray; Arnaud Bourdin; Nicolas Roche

Publisher

Springer Science and Business Media LLC

Published

2022

Language

EN

Field

Medicine (Health Sciences)