Dharun Teja Vujjini, R. M. Salah, A. Alsadoon, P.W.C. Prasa
{"title":"结合自身免疫治疗的混合现实可视化技术在传染病实时跟踪和治疗中的应用研究","authors":"Dharun Teja Vujjini, R. M. Salah, A. Alsadoon, P.W.C. Prasa","doi":"10.1109/CITISIA50690.2020.9371853","DOIUrl":null,"url":null,"abstract":"Healthcare is a key part of the biological process structure in particular semantic recognition of diseases. Critical states of death rates are arranged by determining and activating human epidemics by using smartphone applications for determining and activating human epidemics. Then, it is diagnosed and treat people over autoimmune facility visualized by image processors. The components system is classified into three attributes: Data, Prediction technique, and View. Data are collected from several attributes and resources such as sensors, bit rates, smartphones. While, prediction techniques promote energy responses, decision trees, correlation in the algorithm of mass centric, SVM classifiers, enumeration, error backpropagation, and least square reliefs. Based on several articles, using prediction techniques can be benefited the treating autoimmune therapy by classifying groups and validating criteria. Mixed Reality visualizations based on Image Guided Surgery (IGS) systems increasingly study now. Nevertheless, has not been used in the Operating Room ever so much. It is may due to the result of several factors such as the systems are developed from a technical perspective and rarely evaluated in the field. This paper introduces the Data, Visualization processing, View (DVV) taxonomy which defines each of the major components required for implementing a Mixed Reality IGS system.","PeriodicalId":145272,"journal":{"name":"2020 5th International Conference on Innovative Technologies in Intelligent Systems and Industrial Applications (CITISIA)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Survey on Real-Time Tracking and Treatment of Infectious Diseases Using Mixed Reality in Visualisation Technique with Autoimmune Therapy\",\"authors\":\"Dharun Teja Vujjini, R. M. Salah, A. Alsadoon, P.W.C. Prasa\",\"doi\":\"10.1109/CITISIA50690.2020.9371853\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Healthcare is a key part of the biological process structure in particular semantic recognition of diseases. Critical states of death rates are arranged by determining and activating human epidemics by using smartphone applications for determining and activating human epidemics. Then, it is diagnosed and treat people over autoimmune facility visualized by image processors. The components system is classified into three attributes: Data, Prediction technique, and View. Data are collected from several attributes and resources such as sensors, bit rates, smartphones. While, prediction techniques promote energy responses, decision trees, correlation in the algorithm of mass centric, SVM classifiers, enumeration, error backpropagation, and least square reliefs. Based on several articles, using prediction techniques can be benefited the treating autoimmune therapy by classifying groups and validating criteria. Mixed Reality visualizations based on Image Guided Surgery (IGS) systems increasingly study now. Nevertheless, has not been used in the Operating Room ever so much. It is may due to the result of several factors such as the systems are developed from a technical perspective and rarely evaluated in the field. 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Survey on Real-Time Tracking and Treatment of Infectious Diseases Using Mixed Reality in Visualisation Technique with Autoimmune Therapy
Healthcare is a key part of the biological process structure in particular semantic recognition of diseases. Critical states of death rates are arranged by determining and activating human epidemics by using smartphone applications for determining and activating human epidemics. Then, it is diagnosed and treat people over autoimmune facility visualized by image processors. The components system is classified into three attributes: Data, Prediction technique, and View. Data are collected from several attributes and resources such as sensors, bit rates, smartphones. While, prediction techniques promote energy responses, decision trees, correlation in the algorithm of mass centric, SVM classifiers, enumeration, error backpropagation, and least square reliefs. Based on several articles, using prediction techniques can be benefited the treating autoimmune therapy by classifying groups and validating criteria. Mixed Reality visualizations based on Image Guided Surgery (IGS) systems increasingly study now. Nevertheless, has not been used in the Operating Room ever so much. It is may due to the result of several factors such as the systems are developed from a technical perspective and rarely evaluated in the field. This paper introduces the Data, Visualization processing, View (DVV) taxonomy which defines each of the major components required for implementing a Mixed Reality IGS system.