Use of Deep Neural Networks in the Detection and Automated Classification of Lesions Using Clinical Images in Ophthalmology, Dermatology, and Oral Medicine—A Systematic Review.
Artificial neural networks (ANN) are artificial intelligence (AI) techniques used in the automated recognition and classification of pathological changes from clinical images in areas such as ophthalmology, dermatology, and oral medicine. The combination of enterprise imaging and AI is gaining notor...
| Publicado en: | Journal of Digital Imaging Vol. 36; no. 3; pp. 1060 - 1071 |
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| Autores principales: | , , , , , , , |
| Formato: | research systematic review tables/charts Journal Article |
| Publicado: |
Springer Nature
Jun2023
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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=164473102&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 164473102 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 08971889 DOQ jtl: Journal of Digital Imaging issn: 08971889 maglogo: N pubinfo: dt: Jun2023 vid: 36 iid: 3 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 164473102 161373724 164473102 164473102 10.1007/s10278-023-00775-3 164473102 ppf: 1060 ppct: 11 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Use of Deep Neural Networks in the Detection and Automated Classification of Lesions Using Clinical Images in Ophthalmology, Dermatology, and Oral Medicine—A Systematic Review. aug: au: Gomes, Rita Fabiane Teixeira Schuch, Lauren Frenzel Martins, Manoela Domingues Honório, Emerson Ferreira de Figueiredo, Rodrigo Marques Schmith, Jean Machado, Giovanna Nunes Carrard, Vinicius Coelho affil: Graduate Program in Dentistry, School of Dentistry, Federal University of Rio Grande Do Sul, Barcelos 2492/503, Bairro Santana, CEP 90035-003, Porto Alegre, RS, Brazil sug: subj: Ophthalmology Dermatology Oral Medicine Diagnostic Imaging Classification Diagnosis, Computer Assisted Neural Networks (Computer) Deep Learning Automation Human Systematic Review PubMed Medline Embase Descriptive Statistics Reproducibility of Results ab: Artificial neural networks (ANN) are artificial intelligence (AI) techniques used in the automated recognition and classification of pathological changes from clinical images in areas such as ophthalmology, dermatology, and oral medicine. The combination of enterprise imaging and AI is gaining notoriety for its potential benefits in healthcare areas such as cardiology, dermatology, ophthalmology, pathology, physiatry, radiation oncology, radiology, and endoscopic. The present study aimed to analyze, through a systematic literature review, the application of performance of ANN and deep learning in the recognition and automated classification of lesions from clinical images, when comparing to the human performance. The PRISMA 2020 approach (Preferred Reporting Items for Systematic Reviews and Meta-analyses) was used by searching four databases of studies that reference the use of IA to define the diagnosis of lesions in ophthalmology, dermatology, and oral medicine areas. A quantitative and qualitative analyses of the articles that met the inclusion criteria were performed. The search yielded the inclusion of 60 studies. It was found that the interest in the topic has increased, especially in the last 3 years. We observed that the performance of IA models is promising, with high accuracy, sensitivity, and specificity, most of them had outcomes equivalent to human comparators. The reproducibility of the performance of models in real-life practice has been reported as a critical point. Study designs and results have been progressively improved. IA resources have the potential to contribute to several areas of health. In the coming years, it is likely to be incorporated into everyday life, contributing to the precision and reducing the time required by the diagnostic process. pubtype: Academic Journal doctype: research systematic review tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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