Work

Natural language processing with machine learning methods to analyze unstructured patient-reported outcomes derived from electronic health records: A systematic review

Year: 2023

Type: review

Study design: Systematic Review

Source: Artificial Intelligence in Medicine

DOI: 10.1016/j.artmed.2023.102701

Authors: Jin-ah Sim, Xiaolei Huang, Madeline R. Horan, Christopher M. Stewart, Leslie L. Robison, Melissa M. Hudson, Justin N. Baker, I-Chan Huang

Institutions: St. Jude Children's Research Hospital, Hallym University, University of Memphis, Stanford University

Language: English

Topic: Biomedical Text Mining and Ontologies

Subfield: Molecular Biology

Field: Biochemistry, Genetics and Molecular Biology

Domain: Life Sciences

SDG: Good health and well-being

Open Access status: bronze

Funders: National Science Foundation, National Cancer Institute

Awards: G3036389094, The St. Jude Lifetime Cohort, G6136885517, CRII: III: Metadata-guided Imbalance-Modeling for Robust Computational Healthcare, G637135862

OpenAlex ID: W4388116325

FWCI: 2.118

Cites: 104

Cited by: 85

Related to: 10