Analysis of Pulse Diagnosis Data from a TCM Doctor and a Device by Random Forest

Kiichi Tago; Atsushi Ogihara; Shoji Nishimura; Qun Jin

doi:10.1007/978-3-030-31605-1_6

Analysis of Pulse Diagnosis Data from a TCM Doctor and a Device by Random Forest

Kiichi Tago, Atsushi Ogihara, Shoji Nishimura, Qun Jin

School of Human Sciences

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

1 Citation (Scopus)

Abstract

Pulse diagnosis is a typical diagnosis of Traditional Chinese Medicine (TCM). However, it is not clear if there is any relationship between the result of pulse diagnosis and other health related data. In this study, we investigate this and analyze pulse diagnosis data from a TCM doctor and a pulse diagnostic instrument (PDI) by Random Forest. Subjects’ vital signs and pulse diagnosis data from a TCM doctor are used as training data. We classify vital signs which have the PDI’s diagnoses labels. As a result, classification accuracies were over 60% in all cases. Our experiment results imply that better pulse diagnosis may be made with assistance of personal health data analysis.

Original language	English
Title of host publication	New Frontiers in Artificial Intelligence - JSAI-isAI 2018 Workshops, JURISIN, AI-Biz, SKL, LENLS, IDAA, Revised Selected Papers
Editors	Kazuhiro Kojima, Maki Sakamoto, Koji Mineshima, Ken Satoh
Publisher	Springer
Pages	74-80
Number of pages	7
ISBN (Print)	9783030316044
DOIs	https://doi.org/10.1007/978-3-030-31605-1_6
Publication status	Published - 2019
Event	10th International Symposium of Artificial Intelligence supported by the Japanese Society for Artificial Intelligence, JSAI-isAI 2018 - Yokohama, Japan Duration: 2018 Nov 12 → 2018 Nov 14

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	11717 LNAI
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	10th International Symposium of Artificial Intelligence supported by the Japanese Society for Artificial Intelligence, JSAI-isAI 2018
Country	Japan
City	Yokohama
Period	18/11/12 → 18/11/14

Keywords

Health data analysis
Pulse diagnosis
Random Forest

ASJC Scopus subject areas

Theoretical Computer Science
Computer Science(all)

Access to Document

10.1007/978-3-030-31605-1_6

Fingerprint Dive into the research topics of 'Analysis of Pulse Diagnosis Data from a TCM Doctor and a Device by Random Forest'. Together they form a unique fingerprint.

Cite this

Tago, K., Ogihara, A., Nishimura, S., & Jin, Q. (2019). Analysis of Pulse Diagnosis Data from a TCM Doctor and a Device by Random Forest. In K. Kojima, M. Sakamoto, K. Mineshima, & K. Satoh (Eds.), New Frontiers in Artificial Intelligence - JSAI-isAI 2018 Workshops, JURISIN, AI-Biz, SKL, LENLS, IDAA, Revised Selected Papers (pp. 74-80). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11717 LNAI). Springer. https://doi.org/10.1007/978-3-030-31605-1_6

Analysis of Pulse Diagnosis Data from a TCM Doctor and a Device by Random Forest. / Tago, Kiichi ; Ogihara, Atsushi ; Nishimura, Shoji ; Jin, Qun.

New Frontiers in Artificial Intelligence - JSAI-isAI 2018 Workshops, JURISIN, AI-Biz, SKL, LENLS, IDAA, Revised Selected Papers. ed. / Kazuhiro Kojima; Maki Sakamoto; Koji Mineshima; Ken Satoh. Springer, 2019. p. 74-80 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11717 LNAI).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Tago, K , Ogihara, A , Nishimura, S & Jin, Q 2019, Analysis of Pulse Diagnosis Data from a TCM Doctor and a Device by Random Forest. in K Kojima, M Sakamoto, K Mineshima & K Satoh (eds), New Frontiers in Artificial Intelligence - JSAI-isAI 2018 Workshops, JURISIN, AI-Biz, SKL, LENLS, IDAA, Revised Selected Papers. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 11717 LNAI, Springer, pp. 74-80, 10th International Symposium of Artificial Intelligence supported by the Japanese Society for Artificial Intelligence, JSAI-isAI 2018, Yokohama, Japan, 18/11/12. https://doi.org/10.1007/978-3-030-31605-1_6

Tago K , Ogihara A , Nishimura S , Jin Q. Analysis of Pulse Diagnosis Data from a TCM Doctor and a Device by Random Forest. In Kojima K, Sakamoto M, Mineshima K, Satoh K, editors, New Frontiers in Artificial Intelligence - JSAI-isAI 2018 Workshops, JURISIN, AI-Biz, SKL, LENLS, IDAA, Revised Selected Papers. Springer. 2019. p. 74-80. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-030-31605-1_6

Tago, Kiichi ; Ogihara, Atsushi ; Nishimura, Shoji ; Jin, Qun. / Analysis of Pulse Diagnosis Data from a TCM Doctor and a Device by Random Forest. New Frontiers in Artificial Intelligence - JSAI-isAI 2018 Workshops, JURISIN, AI-Biz, SKL, LENLS, IDAA, Revised Selected Papers. editor / Kazuhiro Kojima ; Maki Sakamoto ; Koji Mineshima ; Ken Satoh. Springer, 2019. pp. 74-80 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{54d08521ae4a4420b3da14fd0f7d3962,

title = "Analysis of Pulse Diagnosis Data from a TCM Doctor and a Device by Random Forest",

abstract = "Pulse diagnosis is a typical diagnosis of Traditional Chinese Medicine (TCM). However, it is not clear if there is any relationship between the result of pulse diagnosis and other health related data. In this study, we investigate this and analyze pulse diagnosis data from a TCM doctor and a pulse diagnostic instrument (PDI) by Random Forest. Subjects{\textquoteright} vital signs and pulse diagnosis data from a TCM doctor are used as training data. We classify vital signs which have the PDI{\textquoteright}s diagnoses labels. As a result, classification accuracies were over 60% in all cases. Our experiment results imply that better pulse diagnosis may be made with assistance of personal health data analysis.",

keywords = "Health data analysis, Pulse diagnosis, Random Forest",

author = "Kiichi Tago and Atsushi Ogihara and Shoji Nishimura and Qun Jin",

year = "2019",

doi = "10.1007/978-3-030-31605-1_6",

language = "English",

isbn = "9783030316044",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

publisher = "Springer",

pages = "74--80",

editor = "Kazuhiro Kojima and Maki Sakamoto and Koji Mineshima and Ken Satoh",

booktitle = "New Frontiers in Artificial Intelligence - JSAI-isAI 2018 Workshops, JURISIN, AI-Biz, SKL, LENLS, IDAA, Revised Selected Papers",

note = "10th International Symposium of Artificial Intelligence supported by the Japanese Society for Artificial Intelligence, JSAI-isAI 2018 ; Conference date: 12-11-2018 Through 14-11-2018",

}

TY - GEN

T1 - Analysis of Pulse Diagnosis Data from a TCM Doctor and a Device by Random Forest

AU - Tago, Kiichi

AU - Ogihara, Atsushi

AU - Nishimura, Shoji

AU - Jin, Qun

PY - 2019

Y1 - 2019

N2 - Pulse diagnosis is a typical diagnosis of Traditional Chinese Medicine (TCM). However, it is not clear if there is any relationship between the result of pulse diagnosis and other health related data. In this study, we investigate this and analyze pulse diagnosis data from a TCM doctor and a pulse diagnostic instrument (PDI) by Random Forest. Subjects’ vital signs and pulse diagnosis data from a TCM doctor are used as training data. We classify vital signs which have the PDI’s diagnoses labels. As a result, classification accuracies were over 60% in all cases. Our experiment results imply that better pulse diagnosis may be made with assistance of personal health data analysis.

AB - Pulse diagnosis is a typical diagnosis of Traditional Chinese Medicine (TCM). However, it is not clear if there is any relationship between the result of pulse diagnosis and other health related data. In this study, we investigate this and analyze pulse diagnosis data from a TCM doctor and a pulse diagnostic instrument (PDI) by Random Forest. Subjects’ vital signs and pulse diagnosis data from a TCM doctor are used as training data. We classify vital signs which have the PDI’s diagnoses labels. As a result, classification accuracies were over 60% in all cases. Our experiment results imply that better pulse diagnosis may be made with assistance of personal health data analysis.

KW - Health data analysis

KW - Pulse diagnosis

KW - Random Forest

UR - http://www.scopus.com/inward/record.url?scp=85075570988&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85075570988&partnerID=8YFLogxK

U2 - 10.1007/978-3-030-31605-1_6

DO - 10.1007/978-3-030-31605-1_6

M3 - Conference contribution

AN - SCOPUS:85075570988

SN - 9783030316044

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 74

EP - 80

BT - New Frontiers in Artificial Intelligence - JSAI-isAI 2018 Workshops, JURISIN, AI-Biz, SKL, LENLS, IDAA, Revised Selected Papers

A2 - Kojima, Kazuhiro

A2 - Sakamoto, Maki

A2 - Mineshima, Koji

A2 - Satoh, Ken

PB - Springer

T2 - 10th International Symposium of Artificial Intelligence supported by the Japanese Society for Artificial Intelligence, JSAI-isAI 2018

Y2 - 12 November 2018 through 14 November 2018

ER -