38 research outputs found

    Using datamining approaches to selectacupoints in acupuncture and Moxibustion for knee osteoarthritis

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    Background: Acupuncture and moxibustion are traditional Chinese medicine therapies commonly used to treat knee osteoarthritis (KOA). Although acupoint selection affects the effectiveness of acupuncture and moxibustion, the basic rules of acupoint selection are little understood and there is a lack of guidelines regarding prescription. In this study, we used data mining approaches to investigate the principles of acupoint selection and provide a framework for formulation prescription in acupuncture and moxibustion for clinical treatment of KOA.Materials and Methods: PubMed, Cochrane Library, Science Citation Index, Wanfang database, VIP database, and China National Knowledge Infrastructure were searched for randomized controlled clinical trials published in English or Chinese from January 1, 2009 to October 1, 2015 evaluating the effect of acupuncture and moxibustion on KOA. Databases were established. Frequency statistics and association rule were used to extract and analyze the data.Results: A total of 876 acupuncture prescriptions and 122 acupoints were included in the analysis. Acupoints were concentrated in acupoints of fourteen meridians. The most frequently used acupoints were Dubi (ST35), Neixiyan (EX-LE4), Yanglingquan (GB34), Xuehai (SP10), Liangqiu (ST34), Zusanli (ST36), Yinlingquan (SP9), and Ashi point. The most frequently used meridian was Stomach Meridian of Foot-Yangming. Acupoints were concentrated mainly in the lower limbs. 42 acupoint pairs occurred frequently, and the top acupoint pairing was Dubi (ST35) and Neixiyan (EX-LE4).Conclusion: Acupoint selection and formulation prescription should focus on locally affected areas, and follow the theory of meridians, which helps establish guidelines for acupuncture and moxibustion in KOA patients.Key words: acupuncture and moxibustion, knee osteoarthritis, acupoint, data mining technolog

    USING DATA MINING APPROACHES TO SELECT ACUPOINTS IN ACUPUNCTURE AND MOXIBUSTION FOR KNEE OSTEOARTHRITIS

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    Background: Acupuncture and moxibustion are traditional Chinese medicine therapies commonly used to treat knee osteoarthritis (KOA). Although acupoint selection affects the effectiveness of acupuncture and moxibustion, the basic rules of acupoint selection are little understood and there is a lack of guidelines regarding prescription. In this study, we used data mining approaches to investigate the principles of acupoint selection and provide a framework for formulation prescription in acupuncture and moxibustion for clinical treatment of KOA. Materials and Methods: PubMed, Cochrane Library, Science Citation Index, Wanfang database, VIP database, and China National Knowledge Infrastructure were searched for randomized controlled clinical trials published in English or Chinese from January 1, 2009 to October 1, 2015 evaluating the effect of acupuncture and moxibustion on KOA. Databases were established. Frequency statistics and association rule were used to extract and analyze the data. Results: A total of 876 acupuncture prescriptions and 122 acupoints were included in the analysis. Acupoints were concentrated in acupoints of fourteen meridians. The most frequently used acupoints were Dubi (ST35), Neixiyan (EX-LE4), Yanglingquan (GB34), Xuehai (SP10), Liangqiu (ST34), Zusanli (ST36), Yinlingquan (SP9), and Ashi point. The most frequently used meridian was Stomach Meridian of Foot-Yangming. Acupoints were concentrated mainly in the lower limbs. 42 acupoint pairs occurred frequently, and the top acupoint pairing was Dubi (ST35) and Neixiyan (EX-LE4). Conclusion: Acupoint selection and formulation prescription should focus on locally affected areas, and follow the theory of meridians, which helps establish guidelines for acupuncture and moxibustion in KOA patients

    ISMAC: An Intelligent System for Customized Clinical Case Management and Analysis

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    Clinical cases are primary and vital evidence for Traditional Chinese Medicine (TCM) clinical research. A great deal of medical knowledge is hidden in the clinical cases of the highly experienced TCM practitioner. With a deep Chinese culture background and years of clinical experience, an experienced TCM specialist usually has his or her unique clinical pattern and diagnosis idea. Preserving huge clinical cases of experienced TCM practitioners as well as exploring the inherent knowledge is then an important but arduous task. The novel system ISMAC (Intelligent System for Management and Analysis of Clinical Cases in TCM) is designed and implemented for customized management and intelligent analysis of TCM clinical data. Customized templates with standard and expert-standard symptoms, diseases, syndromes, and Chinese Medince Formula (CMF) are constructed in ISMAC, according to the clinical diagnosis and treatment characteristic of each TCM specialist. With these templates, clinical cases are archived in order to maintain their original characteristics. Varying data analysis and mining methods, grouped as Basic Analysis, Association Rule, Feature Reduction, Cluster, Pattern Classification, and Pattern Prediction, are implemented in the system. With a flexible dataset retrieval mechanism, ISMAC is a powerful and convenient system for clinical case analysis and clinical knowledge discovery

    Faculty Of Education UNHI

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    Faculty Of Education UNH

    Healthy Living: The European Congress of Epidemiology, 2015

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    The 1989 JSC bibliography of scientific and technical papers

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    This document is a compilation of Lyndon B. Johnson Space Center contributions to the scientific and technical literature in aerospace and life sciences made during calendar year 1989. Citations include NASA formal series reports, journal articles, conference and symposium presentations, papers published in proceedings or other collective works, and seminar and workshop results

    Advances in knowledge discovery and data mining Part II

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    19th Pacific-Asia Conference, PAKDD 2015, Ho Chi Minh City, Vietnam, May 19-22, 2015, Proceedings, Part II</p

    Systematic Approaches for Telemedicine and Data Coordination for COVID-19 in Baja California, Mexico

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    Conference proceedings info: ICICT 2023: 2023 The 6th International Conference on Information and Computer Technologies Raleigh, HI, United States, March 24-26, 2023 Pages 529-542We provide a model for systematic implementation of telemedicine within a large evaluation center for COVID-19 in the area of Baja California, Mexico. Our model is based on human-centric design factors and cross disciplinary collaborations for scalable data-driven enablement of smartphone, cellular, and video Teleconsul-tation technologies to link hospitals, clinics, and emergency medical services for point-of-care assessments of COVID testing, and for subsequent treatment and quar-antine decisions. A multidisciplinary team was rapidly created, in cooperation with different institutions, including: the Autonomous University of Baja California, the Ministry of Health, the Command, Communication and Computer Control Center of the Ministry of the State of Baja California (C4), Colleges of Medicine, and the College of Psychologists. Our objective is to provide information to the public and to evaluate COVID-19 in real time and to track, regional, municipal, and state-wide data in real time that informs supply chains and resource allocation with the anticipation of a surge in COVID-19 cases. RESUMEN Proporcionamos un modelo para la implementación sistemática de la telemedicina dentro de un gran centro de evaluación de COVID-19 en el área de Baja California, México. Nuestro modelo se basa en factores de diseño centrados en el ser humano y colaboraciones interdisciplinarias para la habilitación escalable basada en datos de tecnologías de teleconsulta de teléfonos inteligentes, celulares y video para vincular hospitales, clínicas y servicios médicos de emergencia para evaluaciones de COVID en el punto de atención. pruebas, y para el tratamiento posterior y decisiones de cuarentena. Rápidamente se creó un equipo multidisciplinario, en cooperación con diferentes instituciones, entre ellas: la Universidad Autónoma de Baja California, la Secretaría de Salud, el Centro de Comando, Comunicaciones y Control Informático. de la Secretaría del Estado de Baja California (C4), Facultades de Medicina y Colegio de Psicólogos. Nuestro objetivo es proporcionar información al público y evaluar COVID-19 en tiempo real y rastrear datos regionales, municipales y estatales en tiempo real que informan las cadenas de suministro y la asignación de recursos con la anticipación de un aumento de COVID-19. 19 casos.ICICT 2023: 2023 The 6th International Conference on Information and Computer Technologieshttps://doi.org/10.1007/978-981-99-3236-
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