15 minutes pour comprendre et évaluer un logiciel d’intelligence artificielle appliquée à l’imagerie médicale

Author:

Gautherot M.ORCID,Yepremian S.ORCID,Bretzner M.ORCID,Jacques T.,Hutt A.,Pruvo J.-P.,Kuchcinski G.ORCID,Lopes R.

Publisher

Elsevier BV

Subject

General Medicine

Reference5 articles.

1. Impact of the rise of artificial intelligence in radiology: what do radiologists think?;Waymel;Diagn Interv Imaging,2019

2. CheXNet: radiologist-level pneumonia detection on chest X-rays with deep learning. ArXiv171105225 Cs Stat;Rajpurkar,2017

3. 15minutes pour comprendre les bases de l’intelligence artificielle;Tasu;J Imag Diagn Interv,2019

4. Deep learning for chest radiograph diagnosis: a retrospective comparison of the CheXNeXt algorithm to practicing radiologists;Rajpurkar;PLOS Med,2018

5. Grad-CAM: visual explanations from deep networks via gradient-based localization;Selvaraju;IEEE Int Conf Comput Vis (ICCV),2017

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1. Neighborhood Feature Extraction and Haralick Attributes for Medical Image Analysis: Application to Breast Cancer Mammography Image;2023 10th International Conference on Wireless Networks and Mobile Communications (WINCOM);2023-10-26

2. Medical Imaging;Digital Dictionary;2022-08-26

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