RT Journal Article
SR Electronic
T1 Artificial intelligence outperforms pulmonologists in the interpretation of pulmonary function tests
JF European Respiratory Journal
JO Eur Respir J
FD European Respiratory Society
SP 1801660
DO 10.1183/13993003.01660-2018
A1 Marko Topalovic
A1 Nilakash Das
A1 Pierre- Régis Burgel
A1 Marc Daenen
A1 Eric Derom
A1 Christel Haenebalcke
A1 Rob Janssen
A1 Huib A. M. Kerstjens
A1 Giuseppe Liistro
A1 Renaud Louis
A1 Vincent Ninane
A1 Christophe Pison
A1 Marc Schlesser
A1 Piet Vercauter
A1 Claus F. Vogelmeier
A1 Emiel Wouters
A1 Jokke Wynants
A1 Wim Janssens
A1 ,
YR 2019
UL http://erj.ersjournals.com/content/early/2019/01/30/13993003.01660-2018.abstract
AB The interpretation of pulmonary function tests (PFTs) to diagnose respiratory diseases is built on expert opinion which relies on the recognition of patterns and clinical context for the detection of specific diseases. In the study, we aimed to explore the accuracy and inter-rater variability of pulmonologists when interpreting PFTs and compared it against that of artificial intelligence (AI)-based software which was developed and validated in more than 1500 historical patient cases.120 pulmonologists from 16 European hospitals evaluated 50 cases comprising with PFT and clinical information resulting in 6000 independent interpretations. AI software examined the same data. ATS/ERS guidelines were used as the gold standard for PFT pattern interpretation. The gold standard for diagnosis was derived from clinical history, PFT and all additional tests.The pattern recognition of PFTs by pulmonologists (senior 73%, junior 27%) matched the guidelines in 74.4% (±5.9) of the cases (range: 56–88%). The inter-rater variability of 0.67 (kappa) pointed to a common agreement. Pulmonologists made correct diagnoses in 44.6% (±8.7) of the cases (range: 24–62%) with a large inter-rater variability (kappa=0.35). The AI-based software perfectly matched the PFT pattern interpretations (100%) and assigned a correct diagnosis in 82% of all cases (p<0.0001 for both measures).The interpretation of PFTs by pulmonologists leads to marked variations and errors. AI-based software provides more accurate interpretations and may serve as a powerful decision support tool to improve clinical practice.FootnotesThis manuscript has recently been accepted for publication in the European Respiratory Journal. It is published here in its accepted form prior to copyediting and typesetting by our production team. After these production processes are complete and the authors have approved the resulting proofs, the article will move to the latest issue of the ERJ online. Please open or download the PDF to view this article.Conflict of interest: Dr. Topalovic has nothing to disclose.Conflict of interest: Nilakash Das has nothing to disclose.Conflict of interest: Dr. Burgel reports personal fees from Astra-Zeneca, personal fees from Boehringer Ingelheim, personal fees from Chiesi, personal fees from Novartis, personal fees from TEVA, personal fees from VERTEX, outside the submitted work.Conflict of interest: Dr. Daenen has nothing to disclose.Conflict of interest: Dr. Derom has nothing to disclose.Conflict of interest: Dr. Haenebalcke reports personal fees from NOVARTIS, personal fees from CHIESI, personal fees from GLAXO SMITH KLINE , personal fees from ASTRA ZENECA, outside the submitted work.Conflict of interest: Dr. Janssen has nothing to disclose.Conflict of interest: Dr. Kerstjens has nothing to disclose.Conflict of interest: Dr. Liistro has nothing to disclose.Conflict of interest: Dr. LOUIS reports grants and personal fees from GSK, personal fees from AZ, grants and personal fees from Novartis, grants from Chiesi, outside the submitted work.Conflict of interest: Dr. Ninane has nothing to disclose.Conflict of interest: Dr. Pison has nothing to disclose.Conflict of interest: Marc SchlesserConflict of interest: Dr. Vercauter has nothing to disclose.Conflict of interest: Dr. Vogelmeier reports personal fees from Almirall, grants and personal fees from AstraZeneca, grants and personal fees from Boehringer Ingelheim, grants and personal fees from Chiesi, grants and personal fees from GlaxoSmithKline, grants and personal fees from Grifols, grants and personal fees from Mundipharma, grants and personal fees from Novartis, grants and personal fees from Takeda, personal fees from Cipla, personal fees from Berlin Chemie/Menarini, personal fees from CSL Behring, personal fees from Teva, grants from German Federal Ministry of Education and Research (BMBF) Competence Network Asthma and COPD (ASCONET), grants from Bayer Schering Pharma AG, grants from MSD, grants from Pfizer, outside the submitted work.Conflict of interest: E. WoutersConflict of interest: Dr. Wynants has nothing to disclose.Conflict of interest: Dr. Janssens has nothing to disclose.