Title :
Mining Biomedical Knowledge Using Mutual information ABC
Author :
Li, Guangrong ; Zhang, Xiaodan
Author_Institution :
Sch. of Bus., Hunan Univ., Changsha, China
Abstract :
The novel connection between Raynaud disease and fish oils was uncovered from two disjointed biomedical literature sets by Swanson in 1986. Since then, there have been many approaches to uncover novel connections by mining the biomedical literatures. This paper presents a Mining Biomedical Knowledge method Using Mutual information ABC. For a given starting medical concept, it discovers new, potentially meaningful relations/connection with other concepts that have not been published in the medical literature before. The discovered relations/connections are novel and can be useful for domain expert to conduct new experiment and try new treatment.
Keywords :
data mining; diseases; medical expert systems; Raynaud disease; biomedical knowledge mining; biomedical literature mining; disjointed biomedical literature set; fish oils; medical concept starting; mutual information ABC; potentially meaningful relation; Biomedical measurements; Diseases; Educational institutions; Information science; Marine animals; Mutual information; Oils; biomedical knowledge; mining; mutual information;
Conference_Titel :
Granular Computing (GrC), 2011 IEEE International Conference on
Conference_Location :
Kaohsiung
Print_ISBN :
978-1-4577-0372-0
DOI :
10.1109/GRC.2011.6122711