Advances in Mining Heterogeneous Healthcare Data

Fenglong Ma, Muchao Ye, Junyu Luo, Cao Xiao, Jimeng Sun

Research output: Chapter in Book/Report/Conference proceedingConference contribution


Thanks to the explosion of heterogeneous healthcare data and advanced machine learning and data mining techniques, specifically deep learning methods, we now have an opportunity to make difference in healthcare. In this tutorial, we will present state-of-the-art deep learning methods and their real-world applications, specifically focusing on exploring the unique characteristics of different types of healthcare data. The first half will be spent on introducing recent advances in mining structured healthcare data, including computational phenotyping, disease early detection/risk prediction and treatment recommendation. In the second half, we will focus on challenges specific to the unstructured healthcare data, and introduce advanced deep learning methods in automated ICD coding, understandable medical language translation, clinical trial mining, and medical report generation. This tutorial is intended for students, engineers and researchers who are interested in applying deep learning methods to healthcare, and prerequisite knowledge will be minimal. The tutorial will be concluded with open problems and a Q&A session.

Original languageEnglish (US)
Title of host publicationKDD 2021 - Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining
PublisherAssociation for Computing Machinery
Number of pages2
ISBN (Electronic)9781450383325
StatePublished - Aug 14 2021
Externally publishedYes
Event27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, KDD 2021 - Virtual, Online, Singapore
Duration: Aug 14 2021Aug 18 2021

Publication series

NameProceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining


Conference27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, KDD 2021
CityVirtual, Online


  • deep learning
  • electronic health records
  • health analytics

ASJC Scopus subject areas

  • Software
  • Information Systems


Dive into the research topics of 'Advances in Mining Heterogeneous Healthcare Data'. Together they form a unique fingerprint.

Cite this