2020
DOI: 10.1007/s40368-020-00532-y
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Diagnostic efficacy of and indications for intraoral radiographs in pediatric dentistry: a systematic review

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Cited by 13 publications
(19 citation statements)
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“…EAPD reinforces the use of the specific clinical signs and symptoms for the diagnosis of MIH, as previously described in the earlier EAPD publications (Weerheijm et al 2003 ; Lygidakis et al 2010 ). The use of intraoral X-Rays may add to the diagnosis (Aps et al 2020 ). These criteria are shown in Table 3 .…”
Section: Terminology and Diagnosis Of Mihmentioning
confidence: 99%
“…EAPD reinforces the use of the specific clinical signs and symptoms for the diagnosis of MIH, as previously described in the earlier EAPD publications (Weerheijm et al 2003 ; Lygidakis et al 2010 ). The use of intraoral X-Rays may add to the diagnosis (Aps et al 2020 ). These criteria are shown in Table 3 .…”
Section: Terminology and Diagnosis Of Mihmentioning
confidence: 99%
“…18 Our results are difficult to compare with previous studies, since to our knowledge, no studies assessed the diagnostic accuracy of pulpo-periodontal complications of carious lesions in the particular case of primary molars. 18 Most studies assessed the radiographic diagnosis accuracy of caries detection in permanent teeth 19 and rarely in primary teeth. 20 For studies assessing education methods focusing on interpretation of bitewing or periapical radiographies, these are also rare and again tend to be based on carious lesions in permanent teeth (not pulpo-periodontal complications of carious lesions in primary teeth).…”
Section: Discussionmentioning
confidence: 55%
“…Indeed, even though some papers report strong accuracy and agreement metrics, they are frequently only tested in extracted teeth or cadavers [ 120 , 121 , 122 ]. Other reviews explore intraoral radiology in more detail [ 123 , 124 ]. With advancements in image processing algorithms, imaging devices are ideally placed to leverage these developments to further improve the image analsyis pipeline and provide automatic detection or diagnosis of medical conditions.…”
Section: Discussionmentioning
confidence: 99%