The Generation of a Lung Cancer Health Factor Distribution Using Patient Graphs Constructed From Electronic Medical Records: Retrospective Study.
Anjun ChenRan HuangErman WuRuobing HanJian WenQinghua LiZhiyong ZhangBai-Rong ShenPublished in: Journal of medical Internet research (2022)
By collecting standardized data of thousands of patients with and those without LC from the EMR, it was possible to generate a hospital-wide patient-centered health factor graph for graph search and presentation. The patient graph could be integrated with the UMLS KG for LC and thus enable hospitals to bring continuously updated international standard biomedical KGs from the UMLS for clinical use in hospitals. CDR analysis of the graph of patients with LC generated a CDR-sorted distribution of health factors, in which the top CDR-ranked health factors were concordant with the literature. The resulting distribution of LC health factors can be used to help personalize risk evaluation and preventive screening recommendations.
Keyphrases
- healthcare
- public health
- mental health
- health information
- simultaneous determination
- systematic review
- mass spectrometry
- convolutional neural network
- case report
- emergency department
- machine learning
- big data
- high resolution
- artificial intelligence
- electronic health record
- clinical practice
- wastewater treatment
- solid phase extraction
- clinical evaluation