YouTube for patient education: A deep learning approach for understanding medical knowledge from user-generated videos

Xiao Liu, Bin Zhang, Rema Padman, Anjana Susarla

Research output: Contribution to journalArticlepeer-review

Abstract

YouTube presents an unprecedented opportunity to explore how machine learning methods can improve healthcare information dissemination. We propose an interdisciplinary lens that synthesizes machine learning methods with healthcare informatics themes to address the critical issue of developing a scalable algorithmic solution to evaluate videos from a health literacy and patient education perspective. We develop a deep learning method to understand the level of medical knowledge encoded in YouTube videos. Preliminary results suggest that we can extract medical knowledge from YouTube videos and classify videos according to the embedded knowledge with satisfying performance. Deep learning methods show great promise in knowledge extraction, natural language understanding, and image classification, especially in an era of patient-centric care and precision medicine.

Original languageEnglish (US)
JournalUnknown Journal
StatePublished - Jul 6 2018

Keywords

  • Deep learning
  • Health literacy
  • Patient education
  • User-generated content
  • YouTube

ASJC Scopus subject areas

  • General

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