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Collaboration between explainable artificial intelligence and pulmonologists improves the accuracy of pulmonary function test interpretation

Nilakash Das, Sofie Happaerts, Iwein Gyselinck, Michael Staes, Eric Derom, Guy Brussselle, Felip Burgos, Marco Contoli, Anh Tuan Dinh-Xuan, Frits M. E. Franssen, Sherif Gonem, Neil Greening, Christel Haenebalcke, William D-C. Man, Jorge Moisés, Rudi Peché, Vitalii Poberezhets, Jennifer K. Quint, Michael C. Steiner, Eef Vanderhelst, Mustafa Abdo, Marko Topalovic, Wim Janssens
European Respiratory Journal 2023; DOI: 10.1183/13993003.01720-2022
Nilakash Das
1Laboratory of Respiratory Diseases and Thoracic Surgery, Department of Chronic Diseases Metabolism and Ageing, KU LEUVEN, Leuven, Belgium
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Sofie Happaerts
2Clinical department of Respiratory Diseases, University Hospitals Leuven, Leuven, Belgium
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Iwein Gyselinck
1Laboratory of Respiratory Diseases and Thoracic Surgery, Department of Chronic Diseases Metabolism and Ageing, KU LEUVEN, Leuven, Belgium
2Clinical department of Respiratory Diseases, University Hospitals Leuven, Leuven, Belgium
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Michael Staes
1Laboratory of Respiratory Diseases and Thoracic Surgery, Department of Chronic Diseases Metabolism and Ageing, KU LEUVEN, Leuven, Belgium
2Clinical department of Respiratory Diseases, University Hospitals Leuven, Leuven, Belgium
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Eric Derom
3UZ Gent, University of Ghent, Belgium
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Guy Brussselle
3UZ Gent, University of Ghent, Belgium
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Felip Burgos
4Department of Pulmonary Medicine, Hospital Clinic-Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), University of Barcelona, Barcelona, Spain
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Marco Contoli
5Department of Translational Medicine, University of Ferrara, Ferrara, Italy
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Anh Tuan Dinh-Xuan
6Service de Physiologie-Explorations Fonctionnelles, Assistance Publique-Hôpitaux de Paris, Hôpital Cochin, Université Paris Cité, Paris, France
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  • ORCID record for Anh Tuan Dinh-Xuan
Frits M. E. Franssen
7Department of Respiratory Medicine and School of Nutrition and Translational Research in Metabolism (NUTRIM), Maastricht University Medical Center, Maastricht, Netherlands
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Sherif Gonem
8Nottingham University Hospitals NHS trust, UK
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Neil Greening
9Leicester NIHR Biomedical Research Centre – respiratory, Department of Respiratory Sciences, University of Leicester, UK
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Christel Haenebalcke
10AZ Sint-Jan Brugge-Oostende, Belgium
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William D-C. Man
11National Heart and Lung Institute, Imperial College London, UK
12Royal Brompton and Harefield Clinical Group, Guy's and St.Thomas’ NHS Foundation Trust, UK
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Jorge Moisés
13Biomedical Research Networking Center on Respiratory Diseases (CIBERES), Madrid, Spain
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Rudi Peché
14CHU Charleroi, Belgium
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Vitalii Poberezhets
15Department of Propedeutics of Internal Medicine, National Pirogov Memorial Medical University, Vinnytsya, Ukraine
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Jennifer K. Quint
11National Heart and Lung Institute, Imperial College London, UK
12Royal Brompton and Harefield Clinical Group, Guy's and St.Thomas’ NHS Foundation Trust, UK
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Michael C. Steiner
9Leicester NIHR Biomedical Research Centre – respiratory, Department of Respiratory Sciences, University of Leicester, UK
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Eef Vanderhelst
16University Hospital of Brussels, Vrije Universiteit Brussel, Belgium
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Mustafa Abdo
17LungenClinic Grosshansdorf, Germany
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Marko Topalovic
18ArtiQ NV, Leuven, Belgium
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Wim Janssens
1Laboratory of Respiratory Diseases and Thoracic Surgery, Department of Chronic Diseases Metabolism and Ageing, KU LEUVEN, Leuven, Belgium
2Clinical department of Respiratory Diseases, University Hospitals Leuven, Leuven, Belgium
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  • For correspondence: wim.janssens@uzleuven.be
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Abstract

Rationale Few studies have investigated the collaborative potential between artificial intelligence (AI) and pulmonologists for diagnosing pulmonary disease. We hypothesized that the collaboration between pulmonologist and AI with explanations (explainable AI, XAI) is superior in diagnostic interpretation of pulmonary function tests (PFTs) than a pulmonologist without support.

Materials and methods The study was conducted in two phases, a mono-centre (P1) and a multi-centre intervention study (P2). Each phase utilized two different sets of 24 PFT reports of patients with a clinically validated gold-standard diagnosis. Each PFT was interpreted without (control) and with XAI's suggestions (intervention). Pulmonologists provided a differential diagnosis consisting of a preferential diagnosis and optionally up to three additional diagnoses. Primary endpoint compared accuracy of preferential and additional diagnoses between control and intervention. Secondary endpoints were number of diagnoses in differential diagnosis, diagnostic confidence and inter-rater agreement. We also analysed how XAI influenced pulmonologists’ decisions.

Results In P1 (N=16 pulmonologists), mean preferential and differential diagnostic accuracy significantly increased by 10.4% and 9.4%, respectively between control and intervention (p<0.001). Improvements were somewhat lower but highly significant (p<0.0001) in P2 (5.4% and 8.7% respectively, N=62 pulmonologists). In both phases, the number of diagnoses in differential diagnosis did not reduce, but diagnostic confidence and inter-rater agreement significantly increased during intervention. Pulmonologists updated their decisions with XAI's feedback and consistently improved their baseline performance if AI provided correct predictions.

Conclusion A collaboration between pulmonologist and XAI is better at interpreting PFTs than individual pulmonologists reading without XAI support or XAI alone.

Footnotes

This 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: ND holds a patent on automated quality control of spirometry.

Conflict of interest: SH has nothing to disclose.

Conflict of interest: IG has nothing to disclose.

Conflict of interest: MS has nothing to disclose.

Conflict of interest: ED reports consultancy fees from Chiesi, GSK, AstraZeneca, Boehringer-Ingelheim.

Conflict of interest: GB reports payment honoraria for lectures from Astra Zeneca, Boehringer-Ingelheim, Chiesi, GlaxoSmithKline, Novartis, Sanofi.

Conflict of interest: FB reports consultancy fees from Medical Graphics Coorporation Diagnostics.

Conflict of interest: MC reports grants from University of Ferrara, Chiesi and GlaxoSmithKline, consultancy fees and honoraria from Astra Zeneca, Boehringer-Ingelheim, Chiesi, GlaxoSmithKline, Novartis as well as support for attending meetings from Chiesi, Astra Zeneca, GSK and ALK-ABELLO.

Conflict of interest: ATD has nothing to disclose.

Conflict of interest: FF has nothing to disclose.

Conflict of interest: SG has nothing to disclose.

Conflict of interest: NG has nothing to disclose.

Conflict of interest: CH has nothing to disclose.

Conflict of interest: WM is part funded by a National Institute for Health Research (NIHR) Artificial Intelligence Award, and reports grants from the NIHR and British Lung Foundation, as well as honoraria from Mundipharma, Novartis, European Conference and Incentive Services DMC. WM is the Honorary President of the Association for Respiratory Technology and Physiology (ARTP, UK).

Conflict of interest: JM has nothing to disclose.

Conflict of interest: RP has nothing to disclose.

Conflict of interest: VP has nothing to disclose.

Conflict of interest: JQ reports grants from MRC, HDR UK, GlaxoSmithKline, Astra Zeneca, Chiesi and consultancy fees from Insmed, Evidera.

Conflict of interest: MS has nothing to disclose.

Conflict of interest: EV reports grants from Chiesi and consultancy fees and honoraria from Boehringer Ingelheim, Vertex, GlaxoSmithKline.

Conflict of interest: MA has nothing to disclose.

Conflict of interest: MT is part funded by a National Institute for Health Research (NIHR) Artificial Intelligence Award, he is co-founder and shareholder of ARTIQ.

Conflict of interest: WJ reports grants from Chiesi and AstraZeneca, consultancy and lecture fees from AstraZeneca, Chiesi and GSK, he is co-founder and shareholder of ARTIQ.

This is a PDF-only article. Please click on the PDF link above to read it.

  • Copyright ©The authors 2023.
http://creativecommons.org/licenses/by-nc/4.0/

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Collaboration between explainable artificial intelligence and pulmonologists improves the accuracy of pulmonary function test interpretation
Nilakash Das, Sofie Happaerts, Iwein Gyselinck, Michael Staes, Eric Derom, Guy Brussselle, Felip Burgos, Marco Contoli, Anh Tuan Dinh-Xuan, Frits M. E. Franssen, Sherif Gonem, Neil Greening, Christel Haenebalcke, William D-C. Man, Jorge Moisés, Rudi Peché, Vitalii Poberezhets, Jennifer K. Quint, Michael C. Steiner, Eef Vanderhelst, Mustafa Abdo, Marko Topalovic, Wim Janssens
European Respiratory Journal Jan 2023, 2201720; DOI: 10.1183/13993003.01720-2022

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Collaboration between explainable artificial intelligence and pulmonologists improves the accuracy of pulmonary function test interpretation
Nilakash Das, Sofie Happaerts, Iwein Gyselinck, Michael Staes, Eric Derom, Guy Brussselle, Felip Burgos, Marco Contoli, Anh Tuan Dinh-Xuan, Frits M. E. Franssen, Sherif Gonem, Neil Greening, Christel Haenebalcke, William D-C. Man, Jorge Moisés, Rudi Peché, Vitalii Poberezhets, Jennifer K. Quint, Michael C. Steiner, Eef Vanderhelst, Mustafa Abdo, Marko Topalovic, Wim Janssens
European Respiratory Journal Jan 2023, 2201720; DOI: 10.1183/13993003.01720-2022
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