Telemedicine Supported Chronic Wound Tissue Prediction Using Classification Approaches.
Telemedicine helps to deliver health services electronically to patients with the advancement of communication systems and health informatics. Chronic wound (CW) detection and its healing rate assessment at remote distance is very much difficult due to unavailability of expert doctors. This problem...
| Publicado en: | Journal of Medical Systems Vol. 40; no. 3; pp. 1 - 13 |
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| Autores principales: | , , , , |
| Formato: | equations & formulas pictorial research tables/charts Journal Article |
| Publicado: |
Springer Nature
Mar2016
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=115925260&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 115925260 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 01485598 4N0 jtl: Journal of Medical Systems issn: 01485598 maglogo: N pubinfo: dt: Mar2016 vid: 40 iid: 3 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 115925260 115925260 115925260 10.1007/s10916-015-0424-y 115925260 ppf: 1 ppct: 12 formats: fmt: @attributes: type: P tig: atl: Telemedicine Supported Chronic Wound Tissue Prediction Using Classification Approaches. aug: au: Chakraborty, Chinmay Gupta, Bharat Ghosh, Soumya Das, Dev Chakraborty, Chandan affil: Department of Electronics & Communication Engineering, Birla Institute of Technology, Mesra, Deoghar Campus, Deoghar 814142 India sug: subj: Telemedicine Wounds, Chronic Diagnosis Wounds, Chronic Classification Monitoring, Physiologic Methods Wound Healing Evaluation Human Discriminant Analysis Data Collection Methods Digital Imaging Descriptive Statistics ab: Telemedicine helps to deliver health services electronically to patients with the advancement of communication systems and health informatics. Chronic wound (CW) detection and its healing rate assessment at remote distance is very much difficult due to unavailability of expert doctors. This problem generally affects older ageing people. So there is a need of better assessment facility to the remote people in telemedicine framework. Here we have proposed a CW tissue prediction and diagnosis under telemedicine framework to classify the tissue types using linear discriminant analysis (LDA). The proposed telemedicine based wound tissue prediction (TWTP) model is able to identify wound tissue and correctly predict the wound status with a good degree of accuracy. The overall performance of the proposed wound tissue prediction methodology has been measured based on ground truth images. The proposed methodology will assist the clinicians to take better decision towards diagnosis of CW in terms of quantitative information of three types of tissue composition at low-resource set-up. pubtype: Academic Journal doctype: equations & formulas pictorial research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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