TY - GEN
T1 - A hospital registration system using syndromes' descriptions analysis and information retrieval technology
AU - Yan, Gwo Lang
AU - Chiu, Yu Hsien
AU - Hu, Ling Jen
AU - Tsai, Ming Shih
PY - 2008/12/1
Y1 - 2008/12/1
N2 - correct registration in the hospital can avoid wasting medical resources and shorten the time of diagnoses. The purpose of this research is to build a hospital registration system to help patients register in the hospital. This system can assist patients, who are not familiar with medical topics, to determine which department they should register by the spontaneous descriptions. Patients' spontaneous descriptions of syndromes were transcribed into text formation. These descriptive texts were analyzed by the keywords punctuation process and syndromes' descriptions analysis process to get the important features, including the syndrome words, degree words, affected region of body, frequency, time and place. Then, an information retrieval based department making process was employed to calculate the relation score between each department and these important features. Finally, the system suggested the most possible departments they should register to the patients. In the experiment, 50 descriptions collected from 50 patients are as the input to the system. The preliminary result shows the top one correct rate is 88%. The proposed system also shows the higher performance than the baseline system.
AB - correct registration in the hospital can avoid wasting medical resources and shorten the time of diagnoses. The purpose of this research is to build a hospital registration system to help patients register in the hospital. This system can assist patients, who are not familiar with medical topics, to determine which department they should register by the spontaneous descriptions. Patients' spontaneous descriptions of syndromes were transcribed into text formation. These descriptive texts were analyzed by the keywords punctuation process and syndromes' descriptions analysis process to get the important features, including the syndrome words, degree words, affected region of body, frequency, time and place. Then, an information retrieval based department making process was employed to calculate the relation score between each department and these important features. Finally, the system suggested the most possible departments they should register to the patients. In the experiment, 50 descriptions collected from 50 patients are as the input to the system. The preliminary result shows the top one correct rate is 88%. The proposed system also shows the higher performance than the baseline system.
UR - http://www.scopus.com/inward/record.url?scp=61849117373&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=61849117373&partnerID=8YFLogxK
M3 - Conference contribution
C2 - 19163867
AN - SCOPUS:61849117373
SN - 9781424418152
T3 - Proceedings of the 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08 - "Personalized Healthcare through Technology"
SP - 5113
EP - 5116
BT - Proceedings of the 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08
T2 - 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08
Y2 - 20 August 2008 through 25 August 2008
ER -