PT - JOURNAL ARTICLE AU - Marko Topalovic AU - Nilakash Das AU - Pierre- Régis Burgel AU - Marc Daenen AU - Eric Derom AU - Christel Haenebalcke AU - Rob Janssen AU - Huib A. M. Kerstjens AU - Giuseppe Liistro AU - Renaud Louis AU - Vincent Ninane AU - Christophe Pison AU - Marc Schlesser AU - Piet Vercauter AU - Claus F. Vogelmeier AU - Emiel Wouters AU - Jokke Wynants AU - Wim Janssens ED - , TI - Artificial intelligence outperforms pulmonologists in the interpretation of pulmonary function tests AID - 10.1183/13993003.01660-2018 DP - 2019 Jan 01 TA - European Respiratory Journal PG - 1801660 4099 - http://erj.ersjournals.com/content/early/2019/01/30/13993003.01660-2018.short 4100 - http://erj.ersjournals.com/content/early/2019/01/30/13993003.01660-2018.full 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.