Results 161 to 170 of about 85,328 (269)

Predicting peri‐implantitis incidence and implant failure via risk‐assessment and prognostication tools: A validation study

open access: yesJournal of Periodontology, EarlyView.
Abstract Background Identifying individuals at high risk for developing peri‐implantitis (PI) and then determining the prognosis for implants with PI is crucial for treatment planning. Methods This study longitudinally followed implants from implant placement retrospectively.
Muhammad H. A. Saleh   +9 more
wiley   +1 more source

Risk assessment for canine periodontal disease using a hybrid causal Bayesian network. [PDF]

open access: yesFront Vet Sci
O'Flynn C   +8 more
europepmc   +1 more source

Diagnostic modulation of subgingival proteomic biomarkers by age and smoking habits in periodontitis

open access: yesJournal of Periodontology, EarlyView.
Abstract Background Although age and smoking influence the periodontal proteome, their impact on subgingival biomarkers for diagnosing periodontitis remains unclear. This multicenter study assessed their influence on subgingival proteins for disease detection.
Triana Blanco‐Pintos   +8 more
wiley   +1 more source

Does timing of systemic antibiotics influence periodontal treatment outcomes? A randomized clinical trial

open access: yesJournal of Periodontology, EarlyView.
Abstract Background The aim of this study is to determine whether the timing of metronidazole (MTZ) and amoxicillin (AMX) administration, relative to scaling and root planing (SRP), influences the clinical and microbiological outcomes of periodontal treatment.
Daiane Fermiano   +10 more
wiley   +1 more source

Validate artificial intelligence for the diagnosis of periodontal disease. [PDF]

open access: yesBMC Oral Health
Hameedaldeen A   +3 more
europepmc   +1 more source

Deep learning cone‐beam computed tomography image segmentation for the 3D visualization of mandibular infraosseous periodontal defects

open access: yesJournal of Periodontology, EarlyView.
Abstract Background The accurate assessment of infraosseous periodontal defects is crucial for effective diagnosis and treatment planning. Cone‐beam computed tomography (CBCT) enables detailed imaging of these defects; however, to leverage their full potential, CBCT images must be reconstructed in 3 dimensions (3D).
Daniel Palkovics   +8 more
wiley   +1 more source

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