@inproceedings{fa15e111567e4eafa1c0d225c92457f9,
title = "Towards complementary explanations using deep neural networks",
abstract = "Interpretability is a fundamental property for the acceptance of machine learning models in highly regulated areas. Recently, deep neural networks gained the attention of the scientific community due to their high accuracy in vast classification problems. However, they are still seen as black-box models where it is hard to understand the reasons for the labels that they generate. This paper proposes a deep model with monotonic constraints that generates complementary explanations for its decisions both in terms of style and depth. Furthermore, an objective framework for the evaluation of the explanations is presented. Our method is tested on two biomedical datasets and demonstrates an improvement in relation to traditional models in terms of quality of the explanations generated.",
keywords = "Aesthetics evaluation, Deep neural networks, Dermoscopy, Explanations, Interpretable machine learning",
author = "Wilson Silva and Kelwin Fernandes and Cardoso, {Maria J.} and Cardoso, {Jaime S.}",
note = "Publisher Copyright: {\textcopyright} Springer Nature Switzerland AG 2018.; 1st International Workshop on Machine Learning in Clinical Neuroimaging, MLCN 2018, 1st International Workshop on Deep Learning Fails, DLF 2018, and 1st International Workshop on Interpretability of Machine Intelligence in Medical Image Computing, iMIMIC 2018, held in conjunction with the 21st International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2018 ; Conference date: 16-09-2018 Through 20-09-2018",
year = "2018",
doi = "10.1007/978-3-030-02628-8_15",
language = "English",
isbn = "9783030026271",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer",
pages = "133--140",
editor = "Zeike Taylor and Mauricio Reyes and Cardoso, {M. Jorge} and Silva, {Carlos A.} and Danail Stoyanov and Lena Maier-Hein and Sergio Pereira and Kia, {Seyed Mostafa} and Ipek Oguz and Bennett Landman and Anne Martel and Edouard Duchesnay and Tommy Lofstedt and Marquand, {Andre F.} and Raphael Meier",
booktitle = "Understanding and Interpreting Machine Learning in Medical Image Computing Applications - First International Workshops MLCN 2018, DLF 2018, and iMIMIC 2018, Held in Conjunction with MICCAI 2018, Proceedings",
address = "Germany",
}