Multitask Recalibrated Aggregation Network for Medical Code Prediction

Wei Sun, Shaoxiong Ji*, Erik Cambria, Pekka Marttinen

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

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Abstract

Medical coding translates professionally written medical reports into standardized codes, which is an essential part of medical information systems and health insurance reimbursement. Manual coding by trained human coders is time-consuming and error-prone. Thus, automated coding algorithms have been developed, building especially on the recent advances in machine learning and deep neural networks. To solve the challenges of encoding lengthy and noisy clinical documents and capturing code associations, we propose a multitask recalibrated aggregation network. In particular, multitask learning shares information across different coding schemes and captures the dependencies between different medical codes. Feature recalibration and aggregation in shared modules enhance representation learning for lengthy notes. Experiments with a real-world MIMIC-III dataset show significantly improved predictive performance.

Original languageEnglish
Title of host publicationMachine Learning and Knowledge Discovery in Databases
Subtitle of host publicationApplied Data Science Track - European Conference, ECML PKDD 2021, Proceedings
EditorsYuxiao Dong, Nicolas Kourtellis, Barbara Hammer, Jose A. Lozano
PublisherSpringer Science and Business Media Deutschland GmbH
Pages367-383
Number of pages17
ISBN (Print)9783030865139
DOIs
Publication statusPublished - 2021
MoE publication typeA4 Article in a conference publication
EventEuropean Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases - Virtual, Online
Duration: 13 Sep 202117 Sep 2021

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
PublisherSpringer
Volume12978 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

ConferenceEuropean Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases
Abbreviated titleECML PKDD
CityVirtual, Online
Period13/09/202117/09/2021

Keywords

  • Medical code prediction
  • Multitask learning
  • Recalibrated aggregation network

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