Patient generated health data and electronic health record integration in oncologic surgery: A call for artificial intelligence and machine learning
Laleh G. Melstrom, Andréi S. Rodin, Lorenzo Rossi, Paul Fu, Yuman Fong, Virginia Sun
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.
Topics & Concepts
MedicineElectronic health recordArtificial intelligenceFocus (optics)Health careOncologic surgeryPatient careRelation (database)Patient dataSurgeryNursingComputer scienceDatabaseEconomic growthOpticsEconomicsPhysicsClinical practice guidelines implementationGlobal Cancer Incidence and ScreeningRadiomics and Machine Learning in Medical Imaging