Patient generated health data and electronic health record integration in oncologic surgery: A call for artificial intelligence and machine learning. Review uri icon

Overview

abstract

  • In this review, we aim to assess the current state of science in relation to the integration of patient-generated health data (PGHD) and patient-reported outcomes (PROs) into routine clinical care with a focus on surgical oncology populations. We will also describe the critical role of artificial intelligence and machine-learning methodology in the efficient translation of PGHD, PROs, and traditional outcome measures into meaningful patient care models.

publication date

  • September 24, 2020

Research

keywords

  • Artificial Intelligence
  • Electronic Health Records
  • Machine Learning
  • Neoplasms
  • Patient Generated Health Data
  • Patient Reported Outcome Measures
  • Surgical Oncology

Identity

PubMed Central ID

  • PMC7945992

Scopus Document Identifier

  • 85091453208

Digital Object Identifier (DOI)

  • 10.1002/jso.26232

PubMed ID

  • 32974930

Additional Document Info

volume

  • 123

issue

  • 1