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BioMed Research International 2021The objective of this systematic review was to investigate the quality and outcome of studies into artificial intelligence techniques, analysis, and effect in dentistry.
OBJECTIVE
The objective of this systematic review was to investigate the quality and outcome of studies into artificial intelligence techniques, analysis, and effect in dentistry.
MATERIALS AND METHODS
Using the MeSH keywords: artificial intelligence (AI), dentistry, AI in dentistry, neural networks and dentistry, machine learning, AI dental imaging, and AI treatment recommendations and dentistry. Two investigators performed an electronic search in 5 databases: PubMed/MEDLINE (National Library of Medicine), Scopus (Elsevier), ScienceDirect databases (Elsevier), Web of Science (Clarivate Analytics), and the Cochrane Collaboration (Wiley). The English language articles reporting on AI in different dental specialties were screened for eligibility. Thirty-two full-text articles were selected and systematically analyzed according to a predefined inclusion criterion. These articles were analyzed as per a specific research question, and the relevant data based on article general characteristics, study and control groups, assessment methods, outcomes, and quality assessment were extracted.
RESULTS
The initial search identified 175 articles related to AI in dentistry based on the title and abstracts. The full text of 38 articles was assessed for eligibility to exclude studies not fulfilling the inclusion criteria. Six articles not related to AI in dentistry were excluded. Thirty-two articles were included in the systematic review. It was revealed that AI provides accurate patient management, dental diagnosis, prediction, and decision making. Artificial intelligence appeared as a reliable modality to enhance future implications in the various fields of dentistry, i.e., diagnostic dentistry, patient management, head and neck cancer, restorative dentistry, prosthetic dental sciences, orthodontics, radiology, and periodontics.
CONCLUSION
The included studies describe that AI is a reliable tool to make dental care smooth, better, time-saving, and economical for practitioners. AI benefits them in fulfilling patient demand and expectations. The dentists can use AI to ensure quality treatment, better oral health care outcome, and achieve precision. AI can help to predict failures in clinical scenarios and depict reliable solutions. However, AI is increasing the scope of state-of-the-art models in dentistry but is still under development. Further studies are required to assess the clinical performance of AI techniques in dentistry.
Topics: Artificial Intelligence; Dentistry; Diagnostic Imaging; Forecasting; Humans; Machine Learning; Neural Networks, Computer; Radiography, Dental
PubMed: 34258283
DOI: 10.1155/2021/9751564 -
Journal of Periodontology May 2019The aim of this systematic review and meta-analysis was to compare the clinical efficacy of the early dental implant placement protocol with immediate and delayed dental... (Meta-Analysis)
Meta-Analysis
BACKGROUND
The aim of this systematic review and meta-analysis was to compare the clinical efficacy of the early dental implant placement protocol with immediate and delayed dental implant placement protocols.
METHODS
An electronic and manual search of literature was made to identify clinical studies comparing early implant placement with immediate or delayed placement. Data from the included studies were pooled and quantitative analyses were performed for the implant outcomes reported as the number of failed implants (primary outcome variable) and for changes in peri-implant marginal bone level, peri-implant probing depth, and peri-implant soft tissue level (secondary outcome variables).
RESULTS
Twelve studies met the inclusion criteria. Significant difference in risk of implant failure was found neither between the early and immediate placement protocols (risk difference = -0.018; 95% confidence interval [CI] = -0.06, 0.025; P = 0.416) nor between early and delayed placement protocols (risk difference = -0.008; 95% CI = -0.044, 0.028; P = 0.670). Pooled data of changes in peri-implant marginal bone level demonstrated significantly less marginal bone loss for implants placed using the early placement protocol compared with those placed in fresh extraction sockets (P = 0.001; weighted mean difference = -0.14 mm; 95% CI = -0.22, -0.05). No significant differences were found between the protocols for the other variables.
CONCLUSIONS
The available evidence supports the clinical efficacy of the early implant placement protocol. Present findings indicate that the early implant placement protocol results in implant outcomes similar to immediate and delayed placement protocols and a superior stability of peri-implant hard tissue compared with immediate implant placement.
Topics: Dental Implantation, Endosseous; Dental Implants; Dental Implants, Single-Tooth; Dental Prosthesis, Implant-Supported; Dental Restoration Failure; Immediate Dental Implant Loading; Tooth Extraction; Tooth Socket; Treatment Outcome
PubMed: 30395355
DOI: 10.1002/JPER.18-0338 -
Clinical Oral Investigations Dec 2021The primary aim of this systematic review was to evaluate whether intraoral scanning (IOS) is able to reduce working time and improve patient-reported outcome measures... (Review)
Review
OBJECTIVES
The primary aim of this systematic review was to evaluate whether intraoral scanning (IOS) is able to reduce working time and improve patient-reported outcome measures (PROMs) compared to conventional impression (CI) techniques, taking into account the size of the scanned area. The secondary aim was to verify the effectiveness of IOS procedures based on available prosthodontic outcomes.
MATERIALS AND METHODS
Electronic and manual literature searches were performed to collect evidence concerning the outcomes of IOS and CI performed during the treatment of partially and complete edentulous patients for tooth- or implant-supported restorations. Qualitative analysis was conducted to evaluate the time efficiency and PROMs produced by the two different techniques. Clinical prosthodontic outcomes were analyzed among the included studies when available.
RESULTS
Seventeen studies (9 randomized controlled trials and 8 prospective clinical studies) were selected for qualitative synthesis. The 17 included studies provided data from 430 IOS and 370 CI performed in 437 patients. A total of 7 different IOS systems and their various updated versions were used for digital impressions. The results demonstrated that IOS was overall faster than CI independent of whether quadrant or complete-arch scanning was utilized, regardless of the nature of the restoration (tooth or implant supported). IOS was generally preferred over CI regardless of the size of the scanned area and nature of the restoration (tooth- or implant-supported). Similar prosthodontic outcomes were reported for workflows implementing CI and IOS.
CONCLUSIONS
Within the limitations of this systematic review, IOS is faster than CI, independent of whether a quadrant or complete arch scan is conducted. IOS can improve the patient experience measured by overall preference and comfort and is able to provide reliable prosthodontic outcomes.
CLINICAL RELEVANCE
Reduced procedure working time associated with the use of IOS can improve clinical efficiency and the patient experience during impression procedures. Patient-reported outcome measures (PROMs) are an essential component of evidence-based dental practice as they allow the evaluation of therapeutic modalities from the perspective of the patient. IOS is generally preferred by patients over conventional impressions.
Topics: Computer-Aided Design; Dental Implants; Dental Impression Technique; Humans; Patient Comfort; Prospective Studies; Prosthodontics
PubMed: 34568955
DOI: 10.1007/s00784-021-04157-3 -
The Journal of Prosthetic Dentistry Feb 2023Artificial intelligence (AI) applications are growing in dental implant procedures. The current expansion and performance of AI models in implant dentistry applications...
STATEMENT OF PROBLEM
Artificial intelligence (AI) applications are growing in dental implant procedures. The current expansion and performance of AI models in implant dentistry applications have not yet been systematically documented and analyzed.
PURPOSE
The purpose of this systematic review was to assess the performance of AI models in implant dentistry for implant type recognition, implant success prediction by using patient risk factors and ontology criteria, and implant design optimization combining finite element analysis (FEA) calculations and AI models.
MATERIAL AND METHODS
An electronic systematic review was completed in 5 databases: MEDLINE/PubMed, EMBASE, World of Science, Cochrane, and Scopus. A manual search was also conducted. Peer-reviewed studies that developed AI models for implant type recognition, implant success prediction, and implant design optimization were included. The search strategy included articles published until February 21, 2021. Two investigators independently evaluated the quality of the studies by applying the Joanna Briggs Institute (JBI) Critical Appraisal Checklist for Quasi-Experimental Studies (nonrandomized experimental studies). A third investigator was consulted to resolve lack of consensus.
RESULTS
Seventeen articles were included: 7 investigations analyzed AI models for implant type recognition, 7 studies included AI prediction models for implant success forecast, and 3 studies evaluated AI models for optimization of implant designs. The AI models developed to recognize implant type by using periapical and panoramic images obtained an overall accuracy outcome ranging from 93.8% to 98%. The models to predict osteointegration success or implant success by using different input data varied among the studies, ranging from 62.4% to 80.5%. Finally, the studies that developed AI models to optimize implant designs seem to agree on the applicability of AI models to improve the design of dental implants. This improvement includes minimizing the stress at the implant-bone interface by 36.6% compared with the finite element model; optimizing the implant design porosity, length, and diameter to improve the finite element calculations; or accurately determining the elastic modulus of the implant-bone interface.
CONCLUSIONS
AI models for implant type recognition, implant success prediction, and implant design optimization have demonstrated great potential but are still in development. Additional studies are indispensable to the further development and assessment of the clinical performance of AI models for those implant dentistry applications reviewed.
Topics: Humans; Artificial Intelligence; Dental Implantation, Endosseous; Dental Implants; Porosity
PubMed: 34144789
DOI: 10.1016/j.prosdent.2021.05.008 -
The Journal of Prosthetic Dentistry Nov 2022Artificial intelligence (AI) applications are increasing in restorative procedures. However, the current development and performance of AI in restorative dentistry... (Review)
Review
STATEMENT OF PROBLEM
Artificial intelligence (AI) applications are increasing in restorative procedures. However, the current development and performance of AI in restorative dentistry applications has not yet been systematically documented and analyzed.
PURPOSE
The purpose of this systematic review was to identify and evaluate the ability of AI models in restorative dentistry to diagnose dental caries and vertical tooth fracture, detect tooth preparation margins, and predict restoration failure.
MATERIAL AND METHODS
An electronic systematic review was performed in 5 databases: MEDLINE/PubMed, EMBASE, World of Science, Cochrane, and Scopus. A manual search was also conducted. Studies with AI models were selected based on 4 criteria: diagnosis of dental caries, diagnosis of vertical tooth fracture, detection of the tooth preparation finishing line, and prediction of restoration failure. Two investigators independently evaluated the quality assessment of the studies by applying the Joanna Briggs Institute (JBI) Critical Appraisal Checklist for Quasi-Experimental Studies (nonrandomized experimental studies). A third investigator was consulted to resolve lack of consensus.
RESULTS
A total of 34 articles were included in the review: 29 studies included AI techniques for the diagnosis of dental caries or the elaboration of caries and postsensitivity prediction models, 2 for the diagnosis of vertical tooth fracture, 1 for the tooth preparation finishing line location, and 2 for the prediction of the restoration failure. Among the studies reviewed, the AI models tested obtained a caries diagnosis accuracy ranging from 76% to 88.3%, sensitivity ranging from 73% to 90%, and specificity ranging from 61.5% to 93%. The caries prediction accuracy among the studies ranged from 83.6% to 97.1%. The studies reported an accuracy for the vertical tooth fracture diagnosis ranging from 88.3% to 95.7%. The article using AI models to locate the finishing line reported an accuracy ranging from 90.6% to 97.4%.
CONCLUSIONS
AI models have the potential to provide a powerful tool for assisting in the diagnosis of caries and vertical tooth fracture, detecting the tooth preparation margin, and predicting restoration failure. However, the dental applications of AI models are still in development. Further studies are required to assess the clinical performance of AI models in restorative dentistry.
Topics: Humans; Dental Restoration, Permanent; Dental Caries; Artificial Intelligence; Dentistry; Tooth Fractures
PubMed: 33840515
DOI: 10.1016/j.prosdent.2021.02.010 -
Journal of Dental Research Mar 2012The purpose of this study was to examine the most frequently used criteria to define treatment success in implant dentistry. An electronic MEDLINE/PubMED search was... (Review)
Review
The purpose of this study was to examine the most frequently used criteria to define treatment success in implant dentistry. An electronic MEDLINE/PubMED search was conducted to identify randomized controlled trials and prospective studies reporting on outcomes of implant dentistry. Only studies conducted with roughened surface implants and at least five-year follow-up were included. Data were analyzed for success at the implant level, peri-implant soft tissue, prosthetics, and patient satisfaction. Most frequently reported criteria for success at the implant level were mobility, pain, radiolucency, and peri-implant bone loss (> 1.5 mm), and for success at the peri-implant soft-tissue level, suppuration, and bleeding. The criteria for success at the prosthetic level were the occurrence of technical complications/prosthetic maintenance, adequate function, and esthetics during the five-year period. The criteria at patient satisfaction level were discomfort and paresthesia, satisfaction with appearance, and ability to chew/taste. Success in implant dentistry should ideally evaluate a long-term primary outcome of an implant-prosthetic complex as a whole.
Topics: Benchmarking; Dental Implantation, Endosseous; Dental Prosthesis Design; Dental Prosthesis, Implant-Supported; Humans; Osseointegration; Outcome Assessment, Health Care; Patient Satisfaction
PubMed: 22157097
DOI: 10.1177/0022034511431252 -
Journal of Dentistry Sep 2016A systematic review was conducted to evaluate clinical (survival) and in vitro (fracture strength) studies of endocrown restorations compared to conventional treatments... (Meta-Analysis)
Meta-Analysis Review
OBJECTIVES
A systematic review was conducted to evaluate clinical (survival) and in vitro (fracture strength) studies of endocrown restorations compared to conventional treatments (intraradicular posts, direct composite resin, inlay/onlay).
DATA
This report followed the PRISMA Statement. A total of 8 studies were included in this review.
SOURCES
Two reviewers performed a literature search up to February 2016 in seven databases: PubMed, Web of Science, Scopus, BBO, SciELO, LILACS and IBECS.
STUDY SELECTION
Only clinical trials and in vitro studies that evaluated endocrowns were included. Case reports, case series, pilot studies, reviews and in vitro studies that evaluated properties other than fracture strength of endocrowns were excluded. From the 103 eligible articles, 8 remained in the qualitative analysis (3 clinical trials and 5 in vitro studies), and the meta-analysis was performed for the 5 in vitro studies. A global comparison was performed with random-effects models at a significance level of p<0.05.
RESULTS
Clinical trials showed a success rate of endocrowns varying from 94 to 100%. The global analysis in posterior and anterior teeth demonstrated that endocrowns had higher fracture strength than conventional treatments (p=0.03). However, when comparing endocrowns to conventional treatments only in posterior teeth (subgroup analyses), no statistically significant differences were found between treatments (p=0.07; I(2)=62%).
CONCLUSION
The literature suggests that endocrowns may perform similarly or better than the conventional treatments using intraradicular posts, direct composite resin or inlay/onlay restorations.
CLINICAL SIGNIFICANCE
Although further studies are still necessary to confirm the present findings, endocrowns show potential application for the rehabilitation of severely compromised, endodontically treated teeth.
Topics: Composite Resins; Crowns; Humans; Inlays; Tooth, Nonvital
PubMed: 27421989
DOI: 10.1016/j.jdent.2016.07.005 -
Journal of Dental Research Aug 2016This systematic review and meta-analysis aimed to evaluate the survival rate of ceramic and resin inlays, onlays, and overlays and to identify the complication types... (Meta-Analysis)
Meta-Analysis Review
This systematic review and meta-analysis aimed to evaluate the survival rate of ceramic and resin inlays, onlays, and overlays and to identify the complication types associated with the main clinical outcomes. Two reviewers searched PubMed, EMBASE, and the Cochrane Central Register of Controlled Trials for articles published between 1983 through April 2015, conforming to Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines for systematic reviews. Clinical studies meeting the following criteria were included: 1) studies related to resin and ceramic inlays, onlays, and overlays; 2) prospective, retrospective, or randomized controlled trials conducted in humans; 3) studies with a dropout rate of less than 30%; and 4) studies with a follow-up longer than 5 y. Of 1,389 articles, 14 met the inclusion criteria. The meta-regression indicated that the type of ceramic material (feldspathic porcelain vs. glass-ceramic), study design (retrospective vs. prospective), follow-up time (5 vs. 10 y), and study setting (university vs. private clinic) did not affect the survival rate. Estimated survival rates for glass-ceramics and feldspathic porcelain were between 92% and 95% at 5 y (n = 5,811 restorations) and were 91% at 10 y (n = 2,154 restorations). Failures were related to fractures/chipping (4%), followed by endodontic complications (3%), secondary caries (1%), debonding (1%), and severe marginal staining (0%). Odds ratios (95% confidence intervals) were 0.19 (0.04 to 0.96) and 0.54 (0.17 to 1.69) for pulp vitality and type of tooth involved (premolars vs. molars), respectively. Ceramic inlays, onlays, and overlays showed high survival rates at 5 y and 10 y, and fractures were the most frequent cause of failure.
Topics: Ceramics; Composite Resins; Dental Materials; Dental Restoration Failure; Denture, Overlay; Humans; Inlays
PubMed: 27287305
DOI: 10.1177/0022034516652848 -
Dental Materials : Official Publication... Jun 2015To assess the 5-year survival of metal-ceramic and all-ceramic tooth-supported single crowns (SCs) and to describe the incidence of biological, technical and esthetic... (Review)
Review
OBJECTIVE
To assess the 5-year survival of metal-ceramic and all-ceramic tooth-supported single crowns (SCs) and to describe the incidence of biological, technical and esthetic complications.
METHODS
Medline (PubMed), Embase, Cochrane Central Register of Controlled Trials (CENTRAL) searches (2006-2013) were performed for clinical studies focusing on tooth-supported fixed dental prostheses (FDPs) with a mean follow-up of at least 3 years. This was complimented by an additional hand search and the inclusion of 34 studies from a previous systematic review [1,2]. Survival and complication rates were analyzed using robust Poisson's regression models to obtain summary estimates of 5-year proportions.
RESULTS
Sixty-seven studies reporting on 4663 metal-ceramic and 9434 all-ceramic SCs fulfilled the inclusion criteria. Seventeen studies reported on metal-ceramic crowns, and 54 studies reported on all-ceramic crowns. Meta-analysis of the included studies indicated an estimated survival rate of metal-ceramic SCs of 94.7% (95% CI: 94.1-96.9%) after 5 years. This was similar to the estimated 5-year survival rate of leucit or lithium-disilicate reinforced glass ceramic SCs (96.6%; 95% CI: 94.9-96.7%), of glass infiltrated alumina SCs (94.6%; 95% CI: 92.7-96%) and densely sintered alumina and zirconia SCs (96%; 95% CI: 93.8-97.5%; 92.1%; 95% CI: 82.8-95.6%). In contrast, the 5-year survival rates of feldspathic/silica-based ceramic crowns were lower (p<0.001). When the outcomes in anterior and posterior regions were compared feldspathic/silica-based ceramic and zirconia crowns exhibited significantly lower survival rates in the posterior region (p<0.0001), the other crown types performed similarly. Densely sintered zirconia SCs were more frequently lost due to veneering ceramic fractures than metal-ceramic SCs (p<0.001), and had significantly more loss of retention (p<0.001). In total higher 5 year rates of framework fracture were reported for the all-ceramic SCs than for metal-ceramic SCs.
CONCLUSIONS
Survival rates of most types of all-ceramic SCs were similar to those reported for metal-ceramic SCs, both in anterior and posterior regions. Weaker feldspathic/silica-based ceramics should be limited to applications in the anterior region. Zirconia-based SCs should not be considered as primary option due to their high incidence of technical problems.
Topics: Ceramics; Crowns; Dental Prosthesis Design; Dental Prosthesis, Implant-Supported; Dental Restoration Failure; Esthetics, Dental; Humans; Metal Ceramic Alloys; Metals
PubMed: 25842099
DOI: 10.1016/j.dental.2015.02.011 -
The Journal of Prosthetic Dentistry Apr 2019Different parameters can influence the adaptation of computer-assisted design and computer-assisted manufacturing (CAD-CAM) inlay/onlay restorations. However, systematic... (Review)
Review
STATEMENT OF PROBLEM
Different parameters can influence the adaptation of computer-assisted design and computer-assisted manufacturing (CAD-CAM) inlay/onlay restorations. However, systematic reviews to identify and discuss these parameters are lacking.
PURPOSE
The purpose of this systematic review was to summarize the scientific literature investigating all parameters that can influence both the marginal and internal adaptation of CAD-CAM inlay/onlay restorations.
MATERIAL AND METHODS
An electronic search was conducted by 2 independent reviewers for studies published in English between January 1, 2007 and September 20, 2017 on the PubMed/MEDLINE, Scopus, and Web of Science databases and in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement. Factors investigated in the selected articles included the type of CAD-CAM system, virtual space parameters, version of the software, type of block, luting procedure, type of restoration, sample size and aging procedure, evaluation method, and number of measurement points per specimen.
RESULTS
A total of 162 articles were identified, of which 23 articles met the inclusion criteria. Nine studies investigated adaptation with different restorative materials, 2 evaluated adaptation according to the type of preparation design, 9 compared adaptation before/after thermomechanical loading, and 2 before/after cementation, 1 study investigated marginal adaptation based on whether the optical scan was made intraorally or extraorally, 1 compared adaptation with 5 and 3 axis CAM systems, and 1 assessed adaptation with 4 different intraoral scanners. The risk of bias was high for 7, medium for 15, and low for 1 of the studies reviewed. The high level of heterogeneity across the studies excluded meta-analysis.
CONCLUSIONS
Most of the studies reported clinically acceptable values for marginal adaptation. The performance of a CAD-CAM system is influenced by the type of restorative material. A nonretentive cavity preparation exhibited better adaptation than a retentive preparation. Most studies showed that thermomechanical loading affected the quality of marginal adaptation. Cementation increased marginal discrepancies. No statistically significant difference was found for marginal fit of onlays between intraoral and extraoral optical scans using a stone die. The number of milling axes, the type of digital camera, and the region measured were statistically significant in relation to marginal/internal adaptation. Values of adaptation recorded failed to reproduce the preestablished spacer parameters in the software. Clarification is needed concerning adaptation according to the type of preparation design, the type of material, the choice of intrinsic parameters for the CAD process, the type and shape of milling instruments, and the behavior of the material during milling. Adaptation of CAD-CAM inlay/onlays should be evaluated under clinical conditions.
Topics: Computer-Aided Design; Crowns; Dental Marginal Adaptation; Dental Materials; Dental Prosthesis Design; Inlays
PubMed: 30509548
DOI: 10.1016/j.prosdent.2018.06.006