NDLI: Research on TCM pulse condition identification using probabilistic neural networks

Content Provider	IEEE Xplore Digital Library
Author	Hongxia Guo Binghe Wang
Copyright Year	2010
Description	Author affiliation: Communication Dept. of Engineering College of the Chinese People's Armed Police Force, Xi'an, China (Binghe Wang) \|\| Preps Dept. of Engineering College of the Chinese, People's Armed Police Force, Xi'an, China (Hongxia Guo)
Abstract	The key of objectivity of traditional Chinese Medicine (TCM) pulse condition lies on the objective test and correct recognition for all kinds of pulse conditions. In view of the ambiguity, variety and complexity of TCM pulse conditions, and the shortcomings of the traditional recognition methods and back propagation (BP) neural network method, a kind of TCM pulse-condition recognition method based on probabilistic neural networks (PNN) is put forward. In this research three experienced practitioners of Xi'an TCM Hospital gave us their expert advice and determined the percentage of correct recognition of our PNN method. For the twelve kinds of TCM pulse conditions, we attained an average recognition accuracy of about 93% with PNN method, better than the average recognition accuracy of about 75% attained with the traditional fuzzy cluster method and 87.1% with BP neural network method. The contrastive experiments of the BP neural network method and the PNN method are given. The results show that recognition accuracy of PNN method is out and away higher than that of BP neural network method in high noise circumstances.
Starting Page	2352
Ending Page	2355
File Size	262602
Page Count	4
File Format	PDF
ISBN	9781424464951
e-ISBN	9781424464982
DOI	10.1109/BMEI.2010.5639731
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-10-16
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Training probabilistic neural networks (PNN) Accuracy Noise Artificial neural networks back propagation (BP) neural networks traditional Chinese medicine (TCM) pulse condition Probabilistic logic Pattern recognition Medical diagnostic imaging Bayes minimal risk criterion pattern recognition
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

TCM Pulse-Condition Classification Method Based on BP Neural Network

Genetic Neural Network for Traditional Chinese Medicine

System for Recognition of Chinese Medical Pulse Signal Based on Wavelet Analysis and Back Propagation Neural Network

Leaf shape identification based plant biometrics

Research on diagnostic models of COPD syndromes in TCM based on BP neural network

Speaker recognition based on Probabilistic Neural Network

Classification of IRS LISS-III images using PNN

A new pattern recognition algorithm and its application about tongue fur image classification of Traditional Chinese Medicine

Artificial intelligence meets traditional Chinese medicine: a bridge to opening the magic box of sphygmopalpation for pulse pattern recognition

Research on TCM pulse condition identification using probabilistic neural networks

Similar Documents

TCM Pulse-Condition Classification Method Based on BP Neural Network

Genetic Neural Network for Traditional Chinese Medicine

System for Recognition of Chinese Medical Pulse Signal Based on Wavelet Analysis and Back Propagation Neural Network

Leaf shape identification based plant biometrics

Research on diagnostic models of COPD syndromes in TCM based on BP neural network

Speaker recognition based on Probabilistic Neural Network

Classification of IRS LISS-III images using PNN

A new pattern recognition algorithm and its application about tongue fur image classification of Traditional Chinese Medicine

Artificial intelligence meets traditional Chinese medicine: a bridge to opening the magic box of sphygmopalpation for pulse pattern recognition

Research on TCM pulse condition identification using probabilistic neural networks