Patient generated health data and electronic health record integration in oncologic surgery: A call for artificial intelligence and machine learning.
Laleh G MelstromAndrei S RodinLorenzo A RossiPaul FuYuman FongVirginia SunPublished in: Journal of surgical oncology (2020)
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.
Keyphrases
- artificial intelligence
- electronic health record
- machine learning
- big data
- patient reported outcomes
- healthcare
- public health
- deep learning
- palliative care
- clinical decision support
- case report
- mental health
- adverse drug
- health information
- atrial fibrillation
- prostate cancer
- coronary artery bypass
- surgical site infection
- clinical practice
- risk assessment
- coronary artery disease
- social media
- chronic pain
- robot assisted