ChestView™
AI solution for chest X-ray radiographs
ChestView™ uses deep learning techniques to help clinicians detect subtle abnormalities in chest X-Ray radiographs.
Detect consolidation, pneumothorax, pleural effusion, mediastinal mass and nodule in chest X-Ray radiographs.
Classify and triage exams into three categories: positive, doubt, or negative of anomaly.
Seamlessly integrated results into the PACS through the Incepto Gateway. No additional interface required.
Save time and improve reading comfort
Reduce medical errors and improve diagnostic accuracy
Improve reading comfort
Save time, secure your diagnosis and optimize your workflow with Incepto
Publications
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ECR 2023 Souhail Bennani, et al. Evaluation of radiologists’ performance with and without AI for the detection of thoracic abnormalities on chest X-Ray
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Using AI to Improve Radiologist Performance in Detection of Abnormalities on Chest Radiographs. Souhail Bennani, MD • Nor-Eddine Regnard, MD • Jeanne Ventre, PhD • Louis Lassalle, MD • Toan Nguyen, MD • Alexis Ducarouge, MSc • Lucas Dargent, MD • Enora Guillo, MD • Elodie Gouhier, MD • Sophie-Hélène Zaimi, MD • Emma Canniff, MD • Cécile Malandrin, MD • Philippe Khafagy, MD • Hasmik Koulakian, MD • Marie-Pierre Revel, MD, PhD • Guillaume Chassagnon, MD, PhD. Radiology, Volume 309, Number 3, December 2023
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Learning from the machine: AI assistance is not an effective learning tool for resident education in chest X-ray interpretation. Authors: Gui laume Chassagnon, Nicolas Bi let, Caroline Rutten, Thibault Toussaint, Quentin Cassius de Linval, Mégane Co lin, Leila Lemouchi, Margaux Homps, Mohamed Hedjoudje, Jeanne Ventre, Jules Gregory,Emma Cannif, Nor‐Eddine Regnard, Souhail Bennani, Marie‐Pierre Revel. Journal: European Radiology; Date: 2023
Regulatory
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