AIM
To compare the prognostic performance of an artificial intelligence (AI) model with that of experienced clinicians in predicting tooth loss over a 10-year period.
MATERIALS AND METHODS
An AI model trained on structured clinical and radiographic data was compared with 12 periodontists and 11 general dentists (GDs)...
Pablo Antonio López-Galindo, G. Troiano, M. Serroni et al.· Journal of Clinical Periodon...· 0 citations
AIMS
To quantify the incidence and develop predictive models for postoperative sequelae and complications (POSC) and the need for additional grafting after alveolar ridge augmentation with simultaneous implant placement (SARA).
METHODS
This longitudinal retrospective cohort included adults with ridge deficiencies who...
M. Saleh, Hend Abulatifa, Francesco Fanelli et al.· Journal of Clinical Periodon...· 0 citations
Background: Artificial cranial modification (ACM) in pre-Hispanic Andean populations provides a natural model for investigating whether marked deformation of the cranial vault is associated with corresponding changes in palatal morphology and craniofacial integration. Methods: Three-dimensional geometric morphometrics...
Gregorio Oxilia, F. Paternostro, G. Troiano et al.· Applied Sciences· 0 citations
A multivariate machine learning approach may identify complex signatures with moderate discriminative performance in osteolytic jaw lesions to aid differential diagnosis between developmental and inflammatory Odontogenic Cysts.
Pierluigi Mariani, Francesco Fanelli, Diana Russo et al.· Oral Diseases· 0 citations
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