Abstract
The health care domain is a knowledge-intensive domain. The quality of clinical diagnosis relies mainly on the medical knowledge and experience held by doctors. However, the ability of a single doctor is very limited, so the quality of clinical diagnosis is currently not high. In this paper, an aided diagnosis method based on domain semantic knowledge bases is proposed. Firstly, a domain semantic knowledge base is established by extracting and refining the knowledge of the medicine subject matter domain from the Freebase RDF dumps. Then, based on the semantic knowledge base, the algorithms for calculating the weights of the symptoms in the knowledge base, the relative weights of the diseases related to the input symptom set from a patient, and the related symptom set related to the input symptom set from the patient are proposed. Finally, the clinical medical record data of several common diseases are selected to make an evaluation on the proposed method. For each medical record, the symptom information is extracted from the chief complaint as the patient’s input symptom set. Based on the input symptom set, the method of this paper is used to obtain the list of related diseases and the ranking of disease relative weights. From the disease relevance rankings, the Top 1 (first diagnosis) and Top-3 (first 3 diagnoses) are compared with the doctor’s diagnoses in the medical records. Among them, ovarian cyst has the highest Top-1 and Top-3 hit rates of 67.3% and 89.1%, respectively. Followed by acute upper respiratory tract infection, Top-1 and Top-3 hit rates are 56.6% and 85.2%, respectively. The average Top-1 and Top-3 hit rates are 47.9% and 79.7%, respectively. Compared with the relevant methods, the method of this paper is better. The evaluation results show that based on the domain semantic knowledge base and the aided diagnosis method of diseases constructed in this paper, it is possible to provide aided diagnosis services of a large number of common diseases for general practitioners (especially inexperienced doctors) at the grass-roots level as well as self-diagnosis services of diseases for patients.
Highlights
Diagnosis of diseases is one of the most important aspects of medical activities
The algorithm for calculating wi in [1] has the following two shortcomings: 1) The effects of other symptoms associated with the disease di in the domain semantic knowledge base are not considered
This paper proposes an aided diagnosis method based on domain semantic knowledge bases, including prospective diagnosis and retrospective diagnosis
Summary
Diagnosis of diseases is one of the most important aspects of medical activities. It provides a solid foundation for the treatment and prognosis of patients [1]. The algorithm for calculating wi in [1] has the following two shortcomings: 1) The effects of other symptoms associated with the disease di in the domain semantic knowledge base (not in the patient's input symptom set S) are not considered. This paper proposes two algorithms: the algorithm for calculating the weight ws of the symptom s in the domain semantic knowledge base, and the algorithm for the relative weight wi of the disease di associated with one or more symptoms in the collected patient symptom set S. The last section summarizes this paper and points out further work
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