Attention-Based Explanation in a Deep Learning Model For Classifying Radiology Reports

Autor:	Alberto Lavelli, Roberto Maroldi, Alfonso Gerevini, Ivan Serina, Luca Putelli
Rok vydání:	2021
Předmět:	medicine.medical_specialty Mechanism (biology) Computer science business.industry Deep learning Context (language use) Domain (software engineering) Task (project management) Application domain Delicacy medicine Radiology Artificial intelligence Set (psychology) business
Zdroj:	Artificial Intelligence in Medicine ISBN: 9783030772109 AIME
Popis:	Although deep learning techniques have obtained remarkable results in clinical text analysis, the delicacy of this application domain requires also that these models can be easily understood by the hospital staff. The attention mechanism, which assigns numerical weights representing the contribution of each word to the predictive task, can be exploited for identifying the textual evidence the prediction is based on. In this paper, we investigate the explainability of an attention-based classification model for radiology reports collected from an Italian hospital. The identified explanations are compared with a set of manual annotations made by the domain experts in order to analyze the usefulness of the attention mechanism in our context.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ef0da8021c8919a23048c52e90d34cc6 https://doi.org/10.1007/978-3-030-77211-6_42 Zobrazit plný text záznamu