Human and Deep Learning Predictions of Peripheral Lung Cancer Using a 1.3 mm Video Endoscopic Probe
Iriscope could be a valuable tool in PPNs management, especially for experienced operators. Applied to Iriscope images, DL could enhance overall performance of less experienced physicians in diagnosing malignancy.
Authors
- Benoît Frénay (ORCID: https://orcid.org/0000-0002-7859-2750)
- Rocco Trisolini (ORCID: https://orcid.org/0000-0002-1067-4696)
- C. Farhi
- Luc Thiberville
- Valentin Delchevalerie (ORCID: https://orcid.org/0000-0001-5359-9553)
- Samy Lachkar (ORCID: https://orcid.org/0000-0001-7871-0887)
- Florian Guisier (ORCID: https://orcid.org/0000-0002-8166-7303)
- Edoardo Amante
- Bruno Dumas (ORCID: https://orcid.org/0000-0001-5302-4303)
- Nicolas Mazellier (ORCID: https://orcid.org/0000-0002-4344-9671)
- Mathieu Salaün (ORCID: https://orcid.org/0000-0003-1430-6396)
- Inès Duparc
- Robin Ghyselinck
- Christophe Jubert
Institutions
- Università Cattolica del Sacro Cuore (IT)
- University of Namur (BE)
- Inserm (FR)
- Agostino Gemelli University Polyclinic (IT)
- Normandie Université (FR)
- Laboratoire d'Informatique, du Traitement de l'Information et des Systèmes (FR)
- Université de Rouen Normandie (FR)
Publication Details
- Journal
- Respirology
- Published
- 2025-05-28
- DOI
- https://doi.org/10.1111/resp.70057
- Citations
- 4
- Primary Topic
- Lung Cancer Diagnosis and Treatment
- Type
- article
- Field-Weighted Citation Impact
- 6.07