Benchmarking saliency methods for chest X-ray interpretation

Saliency methods, which produce heat maps that highlight the areas of the medical image that influence model prediction, are often presented to clinicians as an aid in diagnostic decision-making. However, rigorous investigation of the accuracy and reliability of these strategies is necessary before...

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Veröffentlicht in:	Nature machine intelligence 2022-10, Vol.4 (10), p.867-878
Hauptverfasser:	Saporta, Adriel, Gui, Xiaotong, Agrawal, Ashwin, Pareek, Anuj, Truong, Steven Q. H., Nguyen, Chanh D. T., Ngo, Van-Doan, Seekins, Jayne, Blankenberg, Francis G., Ng, Andrew Y., Lungren, Matthew P., Rajpurkar, Pranav
Format:	Artikel
Sprache:	eng
Schlagworte:	631/114/1305 631/114/1564 631/114/2415 692/700/1421/1770 Annotations Automation Benchmarks Datasets Deep learning Engineering Human performance Image segmentation Localization Machine learning Medical imaging Methods Neural networks Pathology Pleural effusion Production methods Reliability Salience
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