2021
DOI: 10.4317/medoral.24238
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Accuracy of computer-aided image analysis in the diagnosis of odontogenic cysts: A systematic review

Abstract: Background This study aimed to search for scientific evidence concerning the accuracy of computer-assisted analysis for diagnosing odontogenic cysts. Material and Methods A systematic review was conducted according to the PRISMA statements and considering eleven databases, including the grey literature. Protocol was registered in PROSPERO (CRD 42020189349). The PECO strategy was used to define the eligibility criteria and only studies involving diagnostic accuracy were … Show more

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Cited by 10 publications
(4 citation statements)
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“…The odontogenic cyst is a lesion in an epithelial lined pathological cavity. Proper diagnosis of odontogenic cysts is critical because different biological behaviors of the various types of cysts require different treatment plans and present significantly different risk for affected patients [3,4].…”
Section: Introductionmentioning
confidence: 99%
“…The odontogenic cyst is a lesion in an epithelial lined pathological cavity. Proper diagnosis of odontogenic cysts is critical because different biological behaviors of the various types of cysts require different treatment plans and present significantly different risk for affected patients [3,4].…”
Section: Introductionmentioning
confidence: 99%
“…A periodontite apical é um processo patológico, podendo ser agudo ou crônico, sintomático ou assintomático e primário ou secundário que ocorre nos tecidos periapicais em detrimento a um quadro infeccioso no sistema de canais radiculares após necrose do tecido pulpar (BITTENCOURT et al, 2021;BERMAN;HARGREAVES;ROTSTEIN, 2021). O epitélio no ápice de um dente não vital presumivelmente pode ser estimulado pela inflamação, formando um verdadeiro cisto revestido por epitélio ou cisto periapical (LOPES; SIQUEIRA, 2020).…”
Section: Introductionunclassified
“…With the fast growth of computer-aided techniques in recent years, the machine learning approach plays an essential role in the detection and characterization of complex clinical conditions by exploring novel prediction algorithms. Many attempts have been made to apply automated machine vision systems using mathematical formulas, image processing, and computational algorithms, to diagnose OKCs [ 10 ]. The application of deep-learning techniques has shown promising results in the diagnosis, prognostication of disease grading, and survival prediction of oral squamous cell carcinoma [ 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 ].…”
Section: Introductionmentioning
confidence: 99%