Medical informatics methods for the clinical evidence extraction.
10.5124/jkma.2012.55.8.741
- Author:
Mi Hwa SONG
1
;
Dong Kyun PARK
;
Young Ho LEE
Author Information
1. U-Healthcare Institute, Gachon University, Incheon, Korea.
- Publication Type:Original Article
- Keywords:
Evidence-based medicine;
Medical informatics computing;
Decision support techniques;
Information storage and retrieval;
Artificial intelligence
- MeSH:
Artificial Intelligence;
Chronic Disease;
Data Mining;
Decision Support Techniques;
Evidence-Based Medicine;
Information Storage and Retrieval;
Medical Informatics;
Medical Informatics Computing;
Patient Care;
Preventive Medicine
- From:Journal of the Korean Medical Association
2012;55(8):741-747
- CountryRepublic of Korea
- Language:Korean
-
Abstract:
Clinical professionals gain new information to assist in patient care when they read the medical literature. Similarly, in clinical preventive medicine, medical science documents that have previously published can be searched and evaluated in order to confirm the scientific support for the clinical preventive medical service offered in order to prevent chronic disease. This paper introduces the medical informatics techniques for knowledge extraction that can become the basis for clinical practice. Particularly, it discusses the clinical document retrieval and knowledge discovery tools that can search for extracting the knowledge which the medical expert desires with data mining techniques. For example, Clinical medical personnel and medical researchers can locate the information from the latest literature rapidly or find and evaluate the scientific basis for the treatment and prevention of infection. This study can be used when they analyze the correlation between accumulated and different type of data and contributes to the detection of new knowledge. Recently, the concern about the visualization of massive data and information is high as the importance of big data has received greater attention. Contributions to this technique and decision support tools will increase gradually due to the way support for decision-making through scientific evidence for the pattern changing disease is evaluated or as one of the clinical practice guidelines is accepted.
