TY - GEN
T1 - Therapeutic category improvement method based on the words appearing in effect-efficacy description
AU - Ishida, Hirotsugu
AU - Nabeta, Keita
AU - Kimura, Masaomi
AU - Ohkura, Michiko
AU - Tsuchiya, Fumito
PY - 2011
Y1 - 2011
N2 - Medical drugs have various efficacies, and are classified focusing on their purpose of use. In Japan, the Ministry of Internal Affairs and Communications gives Japan standard commodity classification (JSCC) numbers to drugs. Therapeutic category numbers are decided based on three digit numbers after the head digits "87". Although the current JSCC numbers are determined based on the revised document "Japan standard commodity classification" compiled in 1990, they have not been revised for 20 years. As a result, when drugs are categorized based on this categorizing system, some drugs are not applicable to any category. As the result, the drugs have been categorized as "other categories" such as "drug for other allergy" or "drug for other cardiovascular disease." The number of such drugs is increasing. However, since it is conceivable that drugs having similar efficacy are often included in other categories, it is necessary that such drugs are classified independently from the "other categories." Therefore, in this study, we analyzed drugs information categorized as "drugs for other cardiovascular disease," and proposed a method of classifying these drugs by using clustering.
AB - Medical drugs have various efficacies, and are classified focusing on their purpose of use. In Japan, the Ministry of Internal Affairs and Communications gives Japan standard commodity classification (JSCC) numbers to drugs. Therapeutic category numbers are decided based on three digit numbers after the head digits "87". Although the current JSCC numbers are determined based on the revised document "Japan standard commodity classification" compiled in 1990, they have not been revised for 20 years. As a result, when drugs are categorized based on this categorizing system, some drugs are not applicable to any category. As the result, the drugs have been categorized as "other categories" such as "drug for other allergy" or "drug for other cardiovascular disease." The number of such drugs is increasing. However, since it is conceivable that drugs having similar efficacy are often included in other categories, it is necessary that such drugs are classified independently from the "other categories." Therefore, in this study, we analyzed drugs information categorized as "drugs for other cardiovascular disease," and proposed a method of classifying these drugs by using clustering.
KW - Clustering
KW - Medical Safety
KW - Therapeutic Category
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U2 - 10.1007/978-3-642-21619-0_23
DO - 10.1007/978-3-642-21619-0_23
M3 - Conference contribution
AN - SCOPUS:79960334795
SN - 9783642216183
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 174
EP - 181
BT - Human-Computer Interaction
T2 - 14th International Conference on Human-Computer Interaction, HCI International 2011
Y2 - 9 July 2011 through 14 July 2011
ER -