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Segawa M, Iizuka N, Ogihara H, Tanaka K, Nakae H, Usuku K, Yamaguchi K, Wada K, Uchizono A, Nakamura Y, Nishida Y, Ueda T, Shiota A, Hasunuma N, Nakahara K, Hebiguchi M, Hamamoto Y. Objective evaluation of tongue diagnosis ability using a tongue diagnosis e-learning/e-assessment system based on a standardized tongue image database. FRONTIERS IN MEDICAL TECHNOLOGY 2023; 5:1050909. [PMID: 36993786 PMCID: PMC10040798 DOI: 10.3389/fmedt.2023.1050909] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2022] [Accepted: 02/10/2023] [Indexed: 03/14/2023] Open
Abstract
BackgroundIn Kampo medicine, tongue examination is used to diagnose the pathological condition “Sho,” but an objective evaluation method for its diagnostic ability has not been established. We constructed a tongue diagnosis electronic learning and evaluation system based on a standardized tongue image database.PurposeThis study aims to verify the practicality of this assessment system by evaluating the tongue diagnosis ability of Kampo specialists (KSs), medical professionals, and students.MethodsIn the first study, we analyzed the answer data of 15 KSs in an 80-question tongue diagnosis test that assesses eight aspects of tongue findings and evaluated the (i) test score, (ii) test difficulty and discrimination index, (iii) diagnostic consistency, and (iv) diagnostic match rate between KSs. In the second study, we administered a 20-question common Kampo test and analyzed the answer data of 107 medical professionals and 56 students that assessed the tongue color discrimination ability and evaluated the (v) correct answer rate, (vi) test difficulty, and (vii) factors related to the correct answer rate.ResultIn the first study, the average test score was 62.2 ± 10.7 points. Twenty-eight questions were difficult (correct answer rate, <50%), 34 were moderate (50%–85%), and 18 were easy (≥85%). Regarding intrarater reliability, the average diagnostic match rate of five KSs involved in database construction was 0.66 ± 0.08, and as for interrater reliability, the diagnostic match rate between the 15 KSs was 0.52 (95% confidence interval, 0.38–0.65) for Gwet's agreement coefficient 1, and the degree of the match rate was moderate. In the second study, the difficulty level of questions was moderate, with a correct rate of 81.3% for medical professionals and 82.1% for students. The discrimination index was good for medical professionals (0.35) and poor for students (0.06). Among medical professionals, the correct answer group of this question had a significantly higher total score on the Kampo common test than the incorrect answer group (85.3 ± 8.4 points vs. 75.8 ± 11.8 points, p < 0.01).ConclusionThis system can objectively evaluate tongue diagnosis ability and has high practicality. Utilizing this system can be expected to contribute to improving learners’ tongue diagnosis ability and standardization of tongue diagnosis.
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Affiliation(s)
- Makoto Segawa
- Department of Kampo Medicine, Yamaguchi University Hospital, Ube, Japan
- Correspondence: Makoto Segawa
| | - Norio Iizuka
- Department of Kampo Medicine, Yamaguchi University Hospital, Ube, Japan
- Yamaguchi Health Examination Center, Ogori-shimogo, Japan
| | - Hiroyuki Ogihara
- Department of Computer Science and Electronic Engineering, National Institute of Technology, Tokuyama Collage, Shunan, Japan
| | - Koichiro Tanaka
- Department of Traditional Medicine, Faculty of Medicine, Toho University, Tokyo, Japan
| | - Hajime Nakae
- Department of Emergency and Critical Care Medicine, Akita University Graduate School of Medicine, Akita, Japan
| | | | - Kojiro Yamaguchi
- Outpatient of Dental Chronic Disease, TANAKA Orthodontic Clinic, Medical Corporation HAYANOKAI, Kagoshima, Japan
| | - Kentaro Wada
- Division of Nephrology and Dialysis, Department of Internal Medicine, Nippon Kokan Fukuyama Hospital, Hiroshima, Japan
| | | | | | - Yoshihiro Nishida
- Department of Obstetrics and Gynecology, Faculty of Medicine, Oita University, Oita, Japan
| | | | - Atsuko Shiota
- Department of Health Sciences, Faculty of Medicine, Kagawa University, Kitagun, Japan
| | - Naoko Hasunuma
- Department of Medical Education, Graduate School of Biomedical and Health Sciences, Hiroshima University, Hiroshima, Japan
| | | | | | - Yoshihiko Hamamoto
- Division of Electrical, Electronic and Information Engineering, Graduate School of Sciences and Technology for Innovation, Yamaguchi University, Ube, Japan
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The Research and Development Thinking on the Status of Artificial Intelligence in Traditional Chinese Medicine. EVIDENCE-BASED COMPLEMENTARY AND ALTERNATIVE MEDICINE 2022; 2022:7644524. [PMID: 35547656 PMCID: PMC9085309 DOI: 10.1155/2022/7644524] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/09/2021] [Revised: 03/04/2022] [Accepted: 04/08/2022] [Indexed: 12/02/2022]
Abstract
With the rapid development and application of artificial intelligence (AI) in medical field, the diagnostic ways of human health and the social medical structures have changed. Based on the concept of holism and the theory of syndrome differentiation and treatment, TCM realizes comprehensive informatization and intelligence with the help of AI technology in data mining, intelligent diagnosis and treatment, intelligent learning, and decision-making. Furthermore, the intelligent research of TCM technology will further promote the improvement in TCM diagnosis and treatment rules and the leaping development of TCM intelligent instruments. In this article, we performed a systematic review of scientific literature about TCM and AI. Moreover, the practical problems of TCM intellectualization, the current situation and demand of TCM, and the influence of AI in the TCM field are discussed by searching for literature using TCM scientific databases, reference lists, expert consultation, and targeted websites. Finally, we look forward to the application prospects of AI and propose a possible future direction of intelligent TCM in the current health-care system in China.
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Chu H, Moon S, Park J, Bak S, Ko Y, Youn BY. The Use of Artificial Intelligence in Complementary and Alternative Medicine: A Systematic Scoping Review. Front Pharmacol 2022; 13:826044. [PMID: 35431917 PMCID: PMC9011141 DOI: 10.3389/fphar.2022.826044] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2021] [Accepted: 03/01/2022] [Indexed: 01/04/2023] Open
Abstract
Background: The development of artificial intelligence (AI) in the medical field has been growing rapidly. As AI models have been introduced in complementary and alternative medicine (CAM), a systematized review must be performed to understand its current status. Objective: To categorize and seek the current usage of AI in CAM. Method: A systematic scoping review was conducted based on the method proposed by the Joanna Briggs Institute. The three databases, PubMed, Embase, and Cochrane Library, were used to find studies regarding AI and CAM. Only English studies from 2000 were included. Studies without mentioning either AI techniques or CAM modalities were excluded along with the non-peer-reviewed studies. A broad-range search strategy was applied to locate all relevant studies. Results: A total of 32 studies were identified, and three main categories were revealed: 1) acupuncture treatment, 2) tongue and lip diagnoses, and 3) herbal medicine. Other CAM modalities were music therapy, meditation, pulse diagnosis, and TCM syndromes. The majority of the studies utilized AI models to predict certain patterns and find reliable computerized models to assist physicians. Conclusion: Although the results from this review have shown the potential use of AI models in CAM, future research ought to focus on verifying and validating the models by performing a large-scale clinical trial to better promote AI in CAM in the era of digital health.
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Affiliation(s)
- Hongmin Chu
- Daecheong Public Health Subcenter, Incheon, South Korea
| | - Seunghwan Moon
- Department of Global Public Health and Korean Medicine Management, Graduate School, Kyung Hee University, Seoul, South Korea
| | - Jeongsu Park
- Department of College of Korean Medicine, Wonkwang University, Iksan, South Korea
| | - Seongjun Bak
- Department of College of Korean Medicine, Wonkwang University, Iksan, South Korea
| | - Youme Ko
- National Institute for Korean Medicine Development (NIKOM), Seoul, South Korea
| | - Bo-Young Youn
- Department of Preventive Medicine, College of Korean Medicine, Kyung Hee University, Seoul, South Korea
- *Correspondence: Bo-Young Youn,
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Segawa M, Iizuka N, Ogihara H, Tanaka K, Nakae H, Usuku K, Hamamoto Y. Construction of a Standardized Tongue Image Database for Diagnostic Education: Development of a Tongue Diagnosis e-Learning System. FRONTIERS IN MEDICAL TECHNOLOGY 2022; 3:760542. [PMID: 35047962 PMCID: PMC8757883 DOI: 10.3389/fmedt.2021.760542] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2021] [Accepted: 11/26/2021] [Indexed: 11/13/2022] Open
Abstract
Tongue examination is an important diagnostic method for judging pathological conditions in Kampo (traditional Japanese medicine), but it is not easy for beginners to learn the diagnostic technique. One reason is that there are few objective diagnostic criteria for tongue examination findings, and the educational method for tongue examination is not standardized in Japan, warranting the need for a tongue image database for e-learning systems that could dramatically improve the efficiency of education. Therefore, we constructed a database comprising tongue images whose findings were determined on the basis of votes given by five Kampo medicine specialists (KMSs) and confirmed the educational usefulness of the database for tongue diagnosis e-learning systems. The study was conducted in the following five steps: development of a tongue imaging collection system, collection of tongue images, evaluation and annotation of tongue images, development of a tongue diagnosis e-learning system, and verification of the educational usefulness of this system. Five KMSs evaluated the tongue images obtained from 125 participants in the following eight aspects: (i) tongue body size, (ii) tongue body color, (iii) tongue body dryness and wetness, (iv) tooth marks on the edge of the tongue, (v) cracks on the surface of the tongue, (vi) thickness of tongue coating, (vii) color of tongue coating, and (viii) dryness and wetness of tongue coating. Medical students (MSs) were given a tongue diagnosis test using an e-learning system after a lecture on tongue diagnosis. The cumulative and individual match rates (%) (individual match rates of 100% (5/5), 80% (4/5), and 60% (3/5) are shown in parentheses, respectively) were as follows: (i) tongue body size: 92.8 (26.4/26.4/40.0); (ii) tongue body color: 83.2 (10.4/20.8/52.0); (iii) tongue body dryness and wetness: 88.8 (13.6/34.4/40.8); (iv) tooth marks on the edge of the tongue: 88.8 (6.4/35.2/47.2); (v) cracks on the surface of the tongue: 96.8 (24.0/35.2/37.6); (vi) thickness of tongue coating: 84.8 (7.2/21.6/56.0); (vii) color of tongue coating: 88.0 (15.2/37.6/35.2); and (viii) dryness and wetness of tongue coating: 74.4 (4.8/19.2/50.4). The test showed that the tongue diagnosis ability of MSs who attended a lecture on tongue diagnosis was almost the same as that of KMSs. We successfully constructed a tongue image database standardized for training specialists on tongue diagnosis and confirmed the educational usefulness of the e-learning system using a database. This database will contribute to the standardization and popularization of Kampo education.
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Affiliation(s)
- Makoto Segawa
- Department of Kampo Medicine, Yamaguchi University Hospital, Ube, Japan
| | - Norio Iizuka
- Department of Kampo Medicine, Yamaguchi University Hospital, Ube, Japan.,Yamaguchi Health Examination Center, Yamaguchi, Japan
| | - Hiroyuki Ogihara
- Division of Electrical, Electronic and Information Engineering, Graduate School of Sciences and Technology for Innovation, Yamaguchi University, Ube, Japan
| | - Koichiro Tanaka
- Department of Traditional Medicine, Faculty of Medicine, Toho University, Tokyo, Japan
| | - Hajime Nakae
- Department of Emergency and Critical Care Medicine, Akita University Graduate School of Medicine, Akita, Japan
| | - Koichiro Usuku
- Department of Medical Information Science and Administrative Planning, Kumamoto University Hospital, Kumamoto, Japan
| | - Yoshihiko Hamamoto
- Division of Electrical, Electronic and Information Engineering, Graduate School of Sciences and Technology for Innovation, Yamaguchi University, Ube, Japan
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