Publications
2021
Bianchi, J; Ruellas, A; Prieto, J C; Li, T; Soroushmehr, R; Najarian, K; Gryak, J; Deleat-Besson, R; Le, C; Yatabe, M; Gurgel, M; Turkestani, N A; Paniagua, B; Cevidanes, L
Decision support systems in temporomandibular Joint osteoarthritis: A review of data science and artificial intelligence applications. Journal Article
In: Seminars in Orthodontics, vol. 27, no. 2, pp. 78-86, 2021.
Abstract | Links | BibTeX | Tags: AAOF, Cone-beam computed tomography, Discrepency Index, malocclusion severity, mandibular asymmetry, orthodontic, Peer Assessment Rating Index, technique, vertical control, x-ray
@article{Bianchi2021,
title = {Decision support systems in temporomandibular Joint osteoarthritis: A review of data science and artificial intelligence applications.},
author = {J Bianchi and A Ruellas and J C Prieto and T Li and R Soroushmehr and K Najarian and J Gryak and R Deleat-Besson and C Le and M Yatabe and M Gurgel and N A Turkestani and B Paniagua and L Cevidanes},
url = {https://pubmed.ncbi.nlm.nih.gov/34305383/},
doi = {10.1053/j.sodo.2021.05.004},
year = {2021},
date = {2021-05-19},
urldate = {2021-05-19},
journal = {Seminars in Orthodontics},
volume = {27},
number = {2},
pages = {78-86},
abstract = {With the exponential growth of computational systems and increased patient data acquisition, dental research faces new challenges to manage a large quantity of information. For this reason, data science approaches are needed for the integrative diagnosis of multifactorial diseases, such as Temporomandibular joint (TMJ) Osteoarthritis (OA). The Data science spectrum includes data capture/acquisition, data processing with optimized web-based storage and management, data analytics involving in-depth statistical analysis, machine learning (ML) approaches, and data communication. Artificial intelligence (AI) plays a crucial role in this process. It consists of developing computational systems that can perform human intelligence tasks, such as disease diagnosis, using many features to help in the decision-making support. Patient's clinical parameters, imaging exams, and molecular data are used as the input in cross-validation tasks, and human annotation/diagnosis is also used as the gold standard to train computational learning models and automatic disease classifiers. This paper aims to review and describe AI and ML techniques to diagnose TMJ OA and data science approaches for imaging processing. We used a web-based system for multi-center data communication, algorithms integration, statistics deployment, and process the computational machine learning models. We successfully show AI and data-science applications using patients' data to improve the TMJ OA diagnosis decision-making towards personalized medicine.},
keywords = {AAOF, Cone-beam computed tomography, Discrepency Index, malocclusion severity, mandibular asymmetry, orthodontic, Peer Assessment Rating Index, technique, vertical control, x-ray},
pubstate = {published},
tppubtype = {article}
}
Turkestani, N Al; Bianchi, J; Deleat-Besson, R; et al,
Clinical decision support systems in orthodontics: A narrative review of data science approaches. Journal Article
In: Orthod Craniofac Res, 2021.
Abstract | Links | BibTeX | Tags: AAOF, clinical orthodontist, Cone-beam computed tomography, Cranial base, craniofacial, hyperdivergent, malocclusion severity, mandibular asymmetry, Posttreatment, technique
@article{Turkestani2021,
title = {Clinical decision support systems in orthodontics: A narrative review of data science approaches.},
author = {N Al Turkestani and J Bianchi and R Deleat-Besson and et al},
url = {https://onlinelibrary.wiley.com/doi/10.1111/ocr.12492},
doi = {10.1111/ocr.12492 },
year = {2021},
date = {2021-05-11},
urldate = {2021-05-11},
journal = {Orthod Craniofac Res},
abstract = {Advancements in technology and data collection generated immense amounts of information from various sources such as health records, clinical examination, imaging, medical devices, as well as experimental and biological data. Proper management and analysis of these data via high-end computing solutions, artificial intelligence and machine learning approaches can assist in extracting meaningful information that enhances population health and well-being. Furthermore, the extracted knowledge can provide new avenues for modern healthcare delivery via clinical decision support systems. This manuscript presents a narrative review of data science approaches for clinical decision support systems in orthodontics. We describe the fundamental components of data science approaches including (a) Data collection, storage and management; (b) Data processing; (C) In-depth data analysis; and (d) Data communication. Then, we introduce a web-based data management platform, the Data Storage for Computation and Integration, for temporomandibular joint and dental clinical decision support systems. },
keywords = {AAOF, clinical orthodontist, Cone-beam computed tomography, Cranial base, craniofacial, hyperdivergent, malocclusion severity, mandibular asymmetry, Posttreatment, technique},
pubstate = {published},
tppubtype = {article}
}
2020
Hardin, A; Valiathan, M; Oh, H; Knigge, R; McNulty, K; Leary, E; Duren, D; Sherwood, R
Clinical implications of age-related change of the mandibular plane angle. Journal Article
In: Orthod Craniofac Res, vol. 1, pp. 50-58, 2020.
Abstract | Links | BibTeX | Tags: Adolescents, Cone-beam computed tomography, Cranial base, craniofacial, fixed appliances, Growth, hyperdivergent, malocclusion severity, Mandibular fixed retainer, vertical control
@article{Hardin2020,
title = {Clinical implications of age-related change of the mandibular plane angle. },
author = {A Hardin and M Valiathan and H Oh and R Knigge and K McNulty and E Leary and D Duren and R Sherwood},
url = {https://pubmed.ncbi.nlm.nih.gov/31465622/},
doi = {10.1111/ocr.12342},
year = {2020},
date = {2020-02-23},
urldate = {2020-02-23},
journal = {Orthod Craniofac Res},
volume = {1},
pages = {50-58},
abstract = {To identify trajectories of ontogenetic change in the mandibular plane angle (MPA) and to describe the influence of sex and other factors on MPA during growth.},
keywords = {Adolescents, Cone-beam computed tomography, Cranial base, craniofacial, fixed appliances, Growth, hyperdivergent, malocclusion severity, Mandibular fixed retainer, vertical control},
pubstate = {published},
tppubtype = {article}
}
2018
Liu, S; Oh, H; Chambers, D; Baumrind, S; Xu, T
Interpreting Weightings of the Peer Assessment Rating Index and the Discrepancy Index across Contexts on Chinese Patients. Journal Article
In: European Journal of Orthodontics, vol. 40, no. 2, pp. 157-163, 2018.
Abstract | Links | BibTeX | Tags: clear aligners, clinical orthodontist, Cone-beam computed tomography, Cranial base, Growth, hyperdivergent, malocclusion severity, mandibular asymmetry, Peer Assessment Rating Index, teaching, vertical control
@article{Liu2017b,
title = {Interpreting Weightings of the Peer Assessment Rating Index and the Discrepancy Index across Contexts on Chinese Patients.},
author = {S Liu and H Oh and D Chambers and S Baumrind and T Xu},
url = {https://pubmed.ncbi.nlm.nih.gov/28575327/},
doi = {10.1093/ejo/cjx043},
year = {2018},
date = {2018-04-06},
urldate = {2018-04-06},
journal = {European Journal of Orthodontics},
volume = {40},
number = {2},
pages = {157-163},
abstract = {Determine optimal weightings of Peer Assessment Rating (PAR) index and Discrepancy Index (DI) for malocclusion severity assessment in Chinese orthodontic patients.},
keywords = {clear aligners, clinical orthodontist, Cone-beam computed tomography, Cranial base, Growth, hyperdivergent, malocclusion severity, mandibular asymmetry, Peer Assessment Rating Index, teaching, vertical control},
pubstate = {published},
tppubtype = {article}
}
2017
Xu, Y; Oh, H; Lagravere-Vich, M
Malocclusion Class II-Division 1 skeletal and dental relationships measured by Cone-Beam Computed Tomography. Journal Article
In: International Journal of Orthodontics, vol. 15, no. 3, pp. 365-387, 2017.
Abstract | Links | BibTeX | Tags: AAOF, anterior openbite, clinical orthodontist, Cone-beam computed tomography, Growth, hyperdivergent, malocclusion severity, Mandibular fixed retainer, pressure tension, retrospective
@article{Xu2017,
title = {Malocclusion Class II-Division 1 skeletal and dental relationships measured by Cone-Beam Computed Tomography. },
author = {Y Xu and H Oh and M Lagravere-Vich},
url = {https://www.sciencedirect.com/science/article/pii/S1761722717300621},
doi = {10.1016/j.ortho.2017.06.014},
year = {2017},
date = {2017-09-00},
journal = {International Journal of Orthodontics},
volume = {15},
number = {3},
pages = {365-387},
abstract = {The purpose of this study was to locate traditionally-used landmarks in two-dimensional (2D) images and newly-suggested ones in three-dimensional (3D) images (cone-beam computer tomographies [CBCTs]) and determine possible relationships between them to categorize patients with Class II-1 malocclusion.},
keywords = {AAOF, anterior openbite, clinical orthodontist, Cone-beam computed tomography, Growth, hyperdivergent, malocclusion severity, Mandibular fixed retainer, pressure tension, retrospective},
pubstate = {published},
tppubtype = {article}
}
Lui, S; Oh, H; Chambers, D; Weng, X; Chen, Q; Baumrind, S; Xu, T
In: Orthodontics and Craniofacial Research, vol. 20, no. 3, pp. 140-145, 2017.
Abstract | Links | BibTeX | Tags: AAOF, extraction, fixed appliances, hyperdivergent, malocclusion severity, Mandibular fixed retainer, Mandibular remodeling, Posttreatment, retrospective, technique, x-ray
@article{Liu2017b,
title = {Validity and reliability of the ABO Discrepancy Index and PAR Index (Peer Assessment Rating) for evaluating malocclusion severity among Chinese orthodontists.},
author = {S Lui and H Oh and D Chambers and X Weng and Q Chen and S Baumrind and T Xu},
url = {https://pubmed.ncbi.nlm.nih.gov/28670875/},
doi = {10.1111/ocr.12195},
year = {2017},
date = {2017-08-00},
journal = {Orthodontics and Craniofacial Research},
volume = {20},
number = {3},
pages = {140-145},
abstract = {To assess the validity of the American Board of Orthodontics Discrepancy Index (ABO-DI) and Peer Assessment Rating (PAR) Index in evaluating malocclusion severity in Chinese orthodontic patients.},
keywords = {AAOF, extraction, fixed appliances, hyperdivergent, malocclusion severity, Mandibular fixed retainer, Mandibular remodeling, Posttreatment, retrospective, technique, x-ray},
pubstate = {published},
tppubtype = {article}
}
Hwang, HS; Oh, MH; Oh, HK
Surgery-first approach in correcting skeletal Class III malocclusion with mandibular asymmetry. Journal Article
In: Am J Orthod Dentofacial Orthop, vol. 152, no. 2, pp. 255-267, 2017.
Abstract | Links | BibTeX | Tags: AAOF, adult, anterior openbite, clinical orthodontist, Cone-beam computed tomography, Cranial base, Discrepency Index, fixed appliances, malocclusion severity, Mandibular fixed retainer, Peer Assessment Rating Index, Posttreatment, pressure tension, retrospective
@article{Hwang2017b,
title = {Surgery-first approach in correcting skeletal Class III malocclusion with mandibular asymmetry. },
author = {HS Hwang and MH Oh and HK Oh},
url = {https://pubmed.ncbi.nlm.nih.gov/28760288/},
doi = {10.1016/j.ajodo.2014.10.040},
year = {2017},
date = {2017-08-00},
journal = {Am J Orthod Dentofacial Orthop},
volume = {152},
number = {2},
pages = {255-267},
abstract = {This case report describes a surgical orthodontic case that used the recently introduced surgery-first approach to correct a severe skeletal Class III malocclusion. A 19-year-old woman presented with severe mandibular prognathism and facial asymmetry; she had been waiting for growth completion in order to pursue surgical correction. After prediction of the postsurgical tooth movement and surgical simulation, 2-jaw surgery that included maxillary advancement and differential mandibular setback was performed using a surgery-first approach. Immediate facial improvement was achieved and postsurgical orthodontic treatment was efficiently carried out. The total treatment time was 16 months. The patient's facial appearance improved significantly and a stable surgical orthodontic outcome was obtained.},
keywords = {AAOF, adult, anterior openbite, clinical orthodontist, Cone-beam computed tomography, Cranial base, Discrepency Index, fixed appliances, malocclusion severity, Mandibular fixed retainer, Peer Assessment Rating Index, Posttreatment, pressure tension, retrospective},
pubstate = {published},
tppubtype = {article}
}
Liu, Siqi; Oh, Heesoo; Chambers, David W.; Baumrind, Sheldon; Xu, Tianmin
In: Orthodontics & Craniofacial Research, vol. 2017, no. 20, pp. 140-145, 2017.
Abstract | Links | BibTeX | Tags: Discrepency Index, malocclusion severity, Peer Assessment Rating Index
@article{Liu2017,
title = {Validity of the American Board of Orthodontics Discrepancy Index and the Peer Assessment Rating Index for comprehensive evaluation of malocclusion severity},
author = {Siqi Liu and Heesoo Oh and David W. Chambers and Sheldon Baumrind and Tianmin Xu},
url = {http://162.214.24.32/~crilorg/wp-content/uploads/2018/11/Validity-and-reliability-of-the-ABO-Discrepancy-Index-and-PAR-Index_2017OCR.pdf},
year = {2017},
date = {2017-07-03},
journal = {Orthodontics & Craniofacial Research},
volume = {2017},
number = {20},
pages = {140-145},
abstract = {Objectives: To assess the validity of the American Board of Orthodontics Discrepancy Index (ABO-DI) and Peer Assessment Rating (PAR) Index in evaluating malocclusion
severity in Chinese orthodontic patients.Setting and Sample Population: A stratified random sample of 120 orthodontic patients based on Angle classification was collected from six university orthodontic centres.
Material and Methods: Sixty-nine orthodontists rated malocclusion severity on a five-point scale by assessing a full set of pre-treatment records for each case and listed reasons for their decision. Their judgement was then compared with ABO-DI and PAR scores determined by three calibrated examiners.
Results: Excellent interexaminer reliability of clinician judgement, ABO-DI and PAR index was demonstrated by the Intraclass Correlation Coefficient (rho= 0.995, 0.990 and 0.964, respectively). Both the ABO-DI and US-PAR index showed good correlation with clinician judgement (r=.700 and r=.707, respectively). There was variability among the different Angle classifications: the ABO-DI showed the highest correlation with clinician judgement in Class II patients (r=.780), whereas the US-PAR index showed the highest correlation with clinician judgement in Class III patients (r=.710). Both indices demonstrated the lowest correlations with clinician judgement in Class I patients.
Conclusion: With strong interexaminer agreement, the panel consensus was used for validating the ABO-DI and US-PAR index for malocclusion severity. Overall, the ABO-DI
and US-PAR index were reliable for measuring malocclusion severity with significantly variable weightings for different Angle classifications. Further modification of the indices for different Angle classification may be indicated.},
keywords = {Discrepency Index, malocclusion severity, Peer Assessment Rating Index},
pubstate = {published},
tppubtype = {article}
}
severity in Chinese orthodontic patients.Setting and Sample Population: A stratified random sample of 120 orthodontic patients based on Angle classification was collected from six university orthodontic centres.
Material and Methods: Sixty-nine orthodontists rated malocclusion severity on a five-point scale by assessing a full set of pre-treatment records for each case and listed reasons for their decision. Their judgement was then compared with ABO-DI and PAR scores determined by three calibrated examiners.
Results: Excellent interexaminer reliability of clinician judgement, ABO-DI and PAR index was demonstrated by the Intraclass Correlation Coefficient (rho= 0.995, 0.990 and 0.964, respectively). Both the ABO-DI and US-PAR index showed good correlation with clinician judgement (r=.700 and r=.707, respectively). There was variability among the different Angle classifications: the ABO-DI showed the highest correlation with clinician judgement in Class II patients (r=.780), whereas the US-PAR index showed the highest correlation with clinician judgement in Class III patients (r=.710). Both indices demonstrated the lowest correlations with clinician judgement in Class I patients.
Conclusion: With strong interexaminer agreement, the panel consensus was used for validating the ABO-DI and US-PAR index for malocclusion severity. Overall, the ABO-DI
and US-PAR index were reliable for measuring malocclusion severity with significantly variable weightings for different Angle classifications. Further modification of the indices for different Angle classification may be indicated.
Oh, H; Baumrind, S; Dugoni, S; Boero, R; Aubert, M; Boyd, R
A retrospective study of Class II mixed-dentition treatment. Journal Article
In: Angle Orthodontist, vol. 87, no. 1, pp. 56-67, 2017.
Abstract | Links | BibTeX | Tags: AAOF, clinical orthodontist, Cone-beam computed tomography, Cranial base, craniofacial, Discrepency Index, Growth, hyperdivergent, malocclusion severity, Mandibular fixed retainer, Mandibular remodeling, mapping, technique, vertical control, x-ray
@article{Oh2017,
title = {A retrospective study of Class II mixed-dentition treatment. },
author = {H Oh and S Baumrind and S Dugoni and R Boero and M Aubert and R Boyd},
url = {https://pubmed.ncbi.nlm.nih.gov/27391205/},
doi = {10.2319/012616-72.1},
year = {2017},
date = {2017-01-00},
journal = {Angle Orthodontist},
volume = {87},
number = {1},
pages = {56-67},
abstract = {To consider the effectiveness of early treatment using one mixed-dentition approach to the correction of moderate and severe Class II malocclusions.},
keywords = {AAOF, clinical orthodontist, Cone-beam computed tomography, Cranial base, craniofacial, Discrepency Index, Growth, hyperdivergent, malocclusion severity, Mandibular fixed retainer, Mandibular remodeling, mapping, technique, vertical control, x-ray},
pubstate = {published},
tppubtype = {article}
}
Bianchi, J; Ruellas, A; Prieto, J C; Li, T; Soroushmehr, R; Najarian, K; Gryak, J; Deleat-Besson, R; Le, C; Yatabe, M; Gurgel, M; Turkestani, N A; Paniagua, B; Cevidanes, L
Decision support systems in temporomandibular Joint osteoarthritis: A review of data science and artificial intelligence applications. Journal Article
In: Seminars in Orthodontics, vol. 27, no. 2, pp. 78-86, 2021.
@article{Bianchi2021,
title = {Decision support systems in temporomandibular Joint osteoarthritis: A review of data science and artificial intelligence applications.},
author = {J Bianchi and A Ruellas and J C Prieto and T Li and R Soroushmehr and K Najarian and J Gryak and R Deleat-Besson and C Le and M Yatabe and M Gurgel and N A Turkestani and B Paniagua and L Cevidanes},
url = {https://pubmed.ncbi.nlm.nih.gov/34305383/},
doi = {10.1053/j.sodo.2021.05.004},
year = {2021},
date = {2021-05-19},
urldate = {2021-05-19},
journal = {Seminars in Orthodontics},
volume = {27},
number = {2},
pages = {78-86},
abstract = {With the exponential growth of computational systems and increased patient data acquisition, dental research faces new challenges to manage a large quantity of information. For this reason, data science approaches are needed for the integrative diagnosis of multifactorial diseases, such as Temporomandibular joint (TMJ) Osteoarthritis (OA). The Data science spectrum includes data capture/acquisition, data processing with optimized web-based storage and management, data analytics involving in-depth statistical analysis, machine learning (ML) approaches, and data communication. Artificial intelligence (AI) plays a crucial role in this process. It consists of developing computational systems that can perform human intelligence tasks, such as disease diagnosis, using many features to help in the decision-making support. Patient's clinical parameters, imaging exams, and molecular data are used as the input in cross-validation tasks, and human annotation/diagnosis is also used as the gold standard to train computational learning models and automatic disease classifiers. This paper aims to review and describe AI and ML techniques to diagnose TMJ OA and data science approaches for imaging processing. We used a web-based system for multi-center data communication, algorithms integration, statistics deployment, and process the computational machine learning models. We successfully show AI and data-science applications using patients' data to improve the TMJ OA diagnosis decision-making towards personalized medicine.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Turkestani, N Al; Bianchi, J; Deleat-Besson, R; et al,
Clinical decision support systems in orthodontics: A narrative review of data science approaches. Journal Article
In: Orthod Craniofac Res, 2021.
@article{Turkestani2021,
title = {Clinical decision support systems in orthodontics: A narrative review of data science approaches.},
author = {N Al Turkestani and J Bianchi and R Deleat-Besson and et al},
url = {https://onlinelibrary.wiley.com/doi/10.1111/ocr.12492},
doi = {10.1111/ocr.12492 },
year = {2021},
date = {2021-05-11},
urldate = {2021-05-11},
journal = {Orthod Craniofac Res},
abstract = {Advancements in technology and data collection generated immense amounts of information from various sources such as health records, clinical examination, imaging, medical devices, as well as experimental and biological data. Proper management and analysis of these data via high-end computing solutions, artificial intelligence and machine learning approaches can assist in extracting meaningful information that enhances population health and well-being. Furthermore, the extracted knowledge can provide new avenues for modern healthcare delivery via clinical decision support systems. This manuscript presents a narrative review of data science approaches for clinical decision support systems in orthodontics. We describe the fundamental components of data science approaches including (a) Data collection, storage and management; (b) Data processing; (C) In-depth data analysis; and (d) Data communication. Then, we introduce a web-based data management platform, the Data Storage for Computation and Integration, for temporomandibular joint and dental clinical decision support systems. },
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Hardin, A; Valiathan, M; Oh, H; Knigge, R; McNulty, K; Leary, E; Duren, D; Sherwood, R
Clinical implications of age-related change of the mandibular plane angle. Journal Article
In: Orthod Craniofac Res, vol. 1, pp. 50-58, 2020.
@article{Hardin2020,
title = {Clinical implications of age-related change of the mandibular plane angle. },
author = {A Hardin and M Valiathan and H Oh and R Knigge and K McNulty and E Leary and D Duren and R Sherwood},
url = {https://pubmed.ncbi.nlm.nih.gov/31465622/},
doi = {10.1111/ocr.12342},
year = {2020},
date = {2020-02-23},
urldate = {2020-02-23},
journal = {Orthod Craniofac Res},
volume = {1},
pages = {50-58},
abstract = {To identify trajectories of ontogenetic change in the mandibular plane angle (MPA) and to describe the influence of sex and other factors on MPA during growth.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Liu, S; Oh, H; Chambers, D; Baumrind, S; Xu, T
Interpreting Weightings of the Peer Assessment Rating Index and the Discrepancy Index across Contexts on Chinese Patients. Journal Article
In: European Journal of Orthodontics, vol. 40, no. 2, pp. 157-163, 2018.
@article{Liu2017b,
title = {Interpreting Weightings of the Peer Assessment Rating Index and the Discrepancy Index across Contexts on Chinese Patients.},
author = {S Liu and H Oh and D Chambers and S Baumrind and T Xu},
url = {https://pubmed.ncbi.nlm.nih.gov/28575327/},
doi = {10.1093/ejo/cjx043},
year = {2018},
date = {2018-04-06},
urldate = {2018-04-06},
journal = {European Journal of Orthodontics},
volume = {40},
number = {2},
pages = {157-163},
abstract = {Determine optimal weightings of Peer Assessment Rating (PAR) index and Discrepancy Index (DI) for malocclusion severity assessment in Chinese orthodontic patients.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Xu, Y; Oh, H; Lagravere-Vich, M
Malocclusion Class II-Division 1 skeletal and dental relationships measured by Cone-Beam Computed Tomography. Journal Article
In: International Journal of Orthodontics, vol. 15, no. 3, pp. 365-387, 2017.
@article{Xu2017,
title = {Malocclusion Class II-Division 1 skeletal and dental relationships measured by Cone-Beam Computed Tomography. },
author = {Y Xu and H Oh and M Lagravere-Vich},
url = {https://www.sciencedirect.com/science/article/pii/S1761722717300621},
doi = {10.1016/j.ortho.2017.06.014},
year = {2017},
date = {2017-09-00},
journal = {International Journal of Orthodontics},
volume = {15},
number = {3},
pages = {365-387},
abstract = {The purpose of this study was to locate traditionally-used landmarks in two-dimensional (2D) images and newly-suggested ones in three-dimensional (3D) images (cone-beam computer tomographies [CBCTs]) and determine possible relationships between them to categorize patients with Class II-1 malocclusion.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Lui, S; Oh, H; Chambers, D; Weng, X; Chen, Q; Baumrind, S; Xu, T
Validity and reliability of the ABO Discrepancy Index and PAR Index (Peer Assessment Rating) for evaluating malocclusion severity among Chinese orthodontists. Journal Article
In: Orthodontics and Craniofacial Research, vol. 20, no. 3, pp. 140-145, 2017.
@article{Liu2017b,
title = {Validity and reliability of the ABO Discrepancy Index and PAR Index (Peer Assessment Rating) for evaluating malocclusion severity among Chinese orthodontists.},
author = {S Lui and H Oh and D Chambers and X Weng and Q Chen and S Baumrind and T Xu},
url = {https://pubmed.ncbi.nlm.nih.gov/28670875/},
doi = {10.1111/ocr.12195},
year = {2017},
date = {2017-08-00},
journal = {Orthodontics and Craniofacial Research},
volume = {20},
number = {3},
pages = {140-145},
abstract = {To assess the validity of the American Board of Orthodontics Discrepancy Index (ABO-DI) and Peer Assessment Rating (PAR) Index in evaluating malocclusion severity in Chinese orthodontic patients.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Hwang, HS; Oh, MH; Oh, HK
Surgery-first approach in correcting skeletal Class III malocclusion with mandibular asymmetry. Journal Article
In: Am J Orthod Dentofacial Orthop, vol. 152, no. 2, pp. 255-267, 2017.
@article{Hwang2017b,
title = {Surgery-first approach in correcting skeletal Class III malocclusion with mandibular asymmetry. },
author = {HS Hwang and MH Oh and HK Oh},
url = {https://pubmed.ncbi.nlm.nih.gov/28760288/},
doi = {10.1016/j.ajodo.2014.10.040},
year = {2017},
date = {2017-08-00},
journal = {Am J Orthod Dentofacial Orthop},
volume = {152},
number = {2},
pages = {255-267},
abstract = {This case report describes a surgical orthodontic case that used the recently introduced surgery-first approach to correct a severe skeletal Class III malocclusion. A 19-year-old woman presented with severe mandibular prognathism and facial asymmetry; she had been waiting for growth completion in order to pursue surgical correction. After prediction of the postsurgical tooth movement and surgical simulation, 2-jaw surgery that included maxillary advancement and differential mandibular setback was performed using a surgery-first approach. Immediate facial improvement was achieved and postsurgical orthodontic treatment was efficiently carried out. The total treatment time was 16 months. The patient's facial appearance improved significantly and a stable surgical orthodontic outcome was obtained.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Liu, Siqi; Oh, Heesoo; Chambers, David W.; Baumrind, Sheldon; Xu, Tianmin
Validity of the American Board of Orthodontics Discrepancy Index and the Peer Assessment Rating Index for comprehensive evaluation of malocclusion severity Journal Article
In: Orthodontics & Craniofacial Research, vol. 2017, no. 20, pp. 140-145, 2017.
@article{Liu2017,
title = {Validity of the American Board of Orthodontics Discrepancy Index and the Peer Assessment Rating Index for comprehensive evaluation of malocclusion severity},
author = {Siqi Liu and Heesoo Oh and David W. Chambers and Sheldon Baumrind and Tianmin Xu},
url = {http://162.214.24.32/~crilorg/wp-content/uploads/2018/11/Validity-and-reliability-of-the-ABO-Discrepancy-Index-and-PAR-Index_2017OCR.pdf},
year = {2017},
date = {2017-07-03},
journal = {Orthodontics & Craniofacial Research},
volume = {2017},
number = {20},
pages = {140-145},
abstract = {Objectives: To assess the validity of the American Board of Orthodontics Discrepancy Index (ABO-DI) and Peer Assessment Rating (PAR) Index in evaluating malocclusion
severity in Chinese orthodontic patients.Setting and Sample Population: A stratified random sample of 120 orthodontic patients based on Angle classification was collected from six university orthodontic centres.
Material and Methods: Sixty-nine orthodontists rated malocclusion severity on a five-point scale by assessing a full set of pre-treatment records for each case and listed reasons for their decision. Their judgement was then compared with ABO-DI and PAR scores determined by three calibrated examiners.
Results: Excellent interexaminer reliability of clinician judgement, ABO-DI and PAR index was demonstrated by the Intraclass Correlation Coefficient (rho= 0.995, 0.990 and 0.964, respectively). Both the ABO-DI and US-PAR index showed good correlation with clinician judgement (r=.700 and r=.707, respectively). There was variability among the different Angle classifications: the ABO-DI showed the highest correlation with clinician judgement in Class II patients (r=.780), whereas the US-PAR index showed the highest correlation with clinician judgement in Class III patients (r=.710). Both indices demonstrated the lowest correlations with clinician judgement in Class I patients.
Conclusion: With strong interexaminer agreement, the panel consensus was used for validating the ABO-DI and US-PAR index for malocclusion severity. Overall, the ABO-DI
and US-PAR index were reliable for measuring malocclusion severity with significantly variable weightings for different Angle classifications. Further modification of the indices for different Angle classification may be indicated.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
severity in Chinese orthodontic patients.Setting and Sample Population: A stratified random sample of 120 orthodontic patients based on Angle classification was collected from six university orthodontic centres.
Material and Methods: Sixty-nine orthodontists rated malocclusion severity on a five-point scale by assessing a full set of pre-treatment records for each case and listed reasons for their decision. Their judgement was then compared with ABO-DI and PAR scores determined by three calibrated examiners.
Results: Excellent interexaminer reliability of clinician judgement, ABO-DI and PAR index was demonstrated by the Intraclass Correlation Coefficient (rho= 0.995, 0.990 and 0.964, respectively). Both the ABO-DI and US-PAR index showed good correlation with clinician judgement (r=.700 and r=.707, respectively). There was variability among the different Angle classifications: the ABO-DI showed the highest correlation with clinician judgement in Class II patients (r=.780), whereas the US-PAR index showed the highest correlation with clinician judgement in Class III patients (r=.710). Both indices demonstrated the lowest correlations with clinician judgement in Class I patients.
Conclusion: With strong interexaminer agreement, the panel consensus was used for validating the ABO-DI and US-PAR index for malocclusion severity. Overall, the ABO-DI
and US-PAR index were reliable for measuring malocclusion severity with significantly variable weightings for different Angle classifications. Further modification of the indices for different Angle classification may be indicated.
Oh, H; Baumrind, S; Dugoni, S; Boero, R; Aubert, M; Boyd, R
A retrospective study of Class II mixed-dentition treatment. Journal Article
In: Angle Orthodontist, vol. 87, no. 1, pp. 56-67, 2017.
@article{Oh2017,
title = {A retrospective study of Class II mixed-dentition treatment. },
author = {H Oh and S Baumrind and S Dugoni and R Boero and M Aubert and R Boyd},
url = {https://pubmed.ncbi.nlm.nih.gov/27391205/},
doi = {10.2319/012616-72.1},
year = {2017},
date = {2017-01-00},
journal = {Angle Orthodontist},
volume = {87},
number = {1},
pages = {56-67},
abstract = {To consider the effectiveness of early treatment using one mixed-dentition approach to the correction of moderate and severe Class II malocclusions.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
2021 |
Bianchi, J; Ruellas, A; Prieto, J C; Li, T; Soroushmehr, R; Najarian, K; Gryak, J; Deleat-Besson, R; Le, C; Yatabe, M; Gurgel, M; Turkestani, N A; Paniagua, B; Cevidanes, L: Decision support systems in temporomandibular Joint osteoarthritis: A review of data science and artificial intelligence applications.. In: Seminars in Orthodontics, vol. 27, no. 2, pp. 78-86, 2021. (Type: Journal Article | Abstract | Links | BibTeX | Tags: AAOF, Cone-beam computed tomography, Discrepency Index, malocclusion severity, mandibular asymmetry, orthodontic, Peer Assessment Rating Index, technique, vertical control, x-ray)@article{Bianchi2021, With the exponential growth of computational systems and increased patient data acquisition, dental research faces new challenges to manage a large quantity of information. For this reason, data science approaches are needed for the integrative diagnosis of multifactorial diseases, such as Temporomandibular joint (TMJ) Osteoarthritis (OA). The Data science spectrum includes data capture/acquisition, data processing with optimized web-based storage and management, data analytics involving in-depth statistical analysis, machine learning (ML) approaches, and data communication. Artificial intelligence (AI) plays a crucial role in this process. It consists of developing computational systems that can perform human intelligence tasks, such as disease diagnosis, using many features to help in the decision-making support. Patient's clinical parameters, imaging exams, and molecular data are used as the input in cross-validation tasks, and human annotation/diagnosis is also used as the gold standard to train computational learning models and automatic disease classifiers. This paper aims to review and describe AI and ML techniques to diagnose TMJ OA and data science approaches for imaging processing. We used a web-based system for multi-center data communication, algorithms integration, statistics deployment, and process the computational machine learning models. We successfully show AI and data-science applications using patients' data to improve the TMJ OA diagnosis decision-making towards personalized medicine. |
Turkestani, N Al; Bianchi, J; Deleat-Besson, R; et al,: Clinical decision support systems in orthodontics: A narrative review of data science approaches.. In: Orthod Craniofac Res, 2021. (Type: Journal Article | Abstract | Links | BibTeX | Tags: AAOF, clinical orthodontist, Cone-beam computed tomography, Cranial base, craniofacial, hyperdivergent, malocclusion severity, mandibular asymmetry, Posttreatment, technique)@article{Turkestani2021, Advancements in technology and data collection generated immense amounts of information from various sources such as health records, clinical examination, imaging, medical devices, as well as experimental and biological data. Proper management and analysis of these data via high-end computing solutions, artificial intelligence and machine learning approaches can assist in extracting meaningful information that enhances population health and well-being. Furthermore, the extracted knowledge can provide new avenues for modern healthcare delivery via clinical decision support systems. This manuscript presents a narrative review of data science approaches for clinical decision support systems in orthodontics. We describe the fundamental components of data science approaches including (a) Data collection, storage and management; (b) Data processing; (C) In-depth data analysis; and (d) Data communication. Then, we introduce a web-based data management platform, the Data Storage for Computation and Integration, for temporomandibular joint and dental clinical decision support systems. |
2020 |
Hardin, A; Valiathan, M; Oh, H; Knigge, R; McNulty, K; Leary, E; Duren, D; Sherwood, R: Clinical implications of age-related change of the mandibular plane angle. . In: Orthod Craniofac Res, vol. 1, pp. 50-58, 2020. (Type: Journal Article | Abstract | Links | BibTeX | Tags: Adolescents, Cone-beam computed tomography, Cranial base, craniofacial, fixed appliances, Growth, hyperdivergent, malocclusion severity, Mandibular fixed retainer, vertical control)@article{Hardin2020, To identify trajectories of ontogenetic change in the mandibular plane angle (MPA) and to describe the influence of sex and other factors on MPA during growth. |
2018 |
Liu, S; Oh, H; Chambers, D; Baumrind, S; Xu, T: Interpreting Weightings of the Peer Assessment Rating Index and the Discrepancy Index across Contexts on Chinese Patients.. In: European Journal of Orthodontics, vol. 40, no. 2, pp. 157-163, 2018. (Type: Journal Article | Abstract | Links | BibTeX | Tags: clear aligners, clinical orthodontist, Cone-beam computed tomography, Cranial base, Growth, hyperdivergent, malocclusion severity, mandibular asymmetry, Peer Assessment Rating Index, teaching, vertical control)@article{Liu2017b, Determine optimal weightings of Peer Assessment Rating (PAR) index and Discrepancy Index (DI) for malocclusion severity assessment in Chinese orthodontic patients. |
2017 |
Xu, Y; Oh, H; Lagravere-Vich, M: Malocclusion Class II-Division 1 skeletal and dental relationships measured by Cone-Beam Computed Tomography. . In: International Journal of Orthodontics, vol. 15, no. 3, pp. 365-387, 2017. (Type: Journal Article | Abstract | Links | BibTeX | Tags: AAOF, anterior openbite, clinical orthodontist, Cone-beam computed tomography, Growth, hyperdivergent, malocclusion severity, Mandibular fixed retainer, pressure tension, retrospective)@article{Xu2017, The purpose of this study was to locate traditionally-used landmarks in two-dimensional (2D) images and newly-suggested ones in three-dimensional (3D) images (cone-beam computer tomographies [CBCTs]) and determine possible relationships between them to categorize patients with Class II-1 malocclusion. |
Lui, S; Oh, H; Chambers, D; Weng, X; Chen, Q; Baumrind, S; Xu, T: Validity and reliability of the ABO Discrepancy Index and PAR Index (Peer Assessment Rating) for evaluating malocclusion severity among Chinese orthodontists.. In: Orthodontics and Craniofacial Research, vol. 20, no. 3, pp. 140-145, 2017. (Type: Journal Article | Abstract | Links | BibTeX | Tags: AAOF, extraction, fixed appliances, hyperdivergent, malocclusion severity, Mandibular fixed retainer, Mandibular remodeling, Posttreatment, retrospective, technique, x-ray)@article{Liu2017b, To assess the validity of the American Board of Orthodontics Discrepancy Index (ABO-DI) and Peer Assessment Rating (PAR) Index in evaluating malocclusion severity in Chinese orthodontic patients. |
Hwang, HS; Oh, MH; Oh, HK: Surgery-first approach in correcting skeletal Class III malocclusion with mandibular asymmetry. . In: Am J Orthod Dentofacial Orthop, vol. 152, no. 2, pp. 255-267, 2017. (Type: Journal Article | Abstract | Links | BibTeX | Tags: AAOF, adult, anterior openbite, clinical orthodontist, Cone-beam computed tomography, Cranial base, Discrepency Index, fixed appliances, malocclusion severity, Mandibular fixed retainer, Peer Assessment Rating Index, Posttreatment, pressure tension, retrospective)@article{Hwang2017b, This case report describes a surgical orthodontic case that used the recently introduced surgery-first approach to correct a severe skeletal Class III malocclusion. A 19-year-old woman presented with severe mandibular prognathism and facial asymmetry; she had been waiting for growth completion in order to pursue surgical correction. After prediction of the postsurgical tooth movement and surgical simulation, 2-jaw surgery that included maxillary advancement and differential mandibular setback was performed using a surgery-first approach. Immediate facial improvement was achieved and postsurgical orthodontic treatment was efficiently carried out. The total treatment time was 16 months. The patient's facial appearance improved significantly and a stable surgical orthodontic outcome was obtained. |
Liu, Siqi; Oh, Heesoo; Chambers, David W.; Baumrind, Sheldon; Xu, Tianmin: Validity of the American Board of Orthodontics Discrepancy Index and the Peer Assessment Rating Index for comprehensive evaluation of malocclusion severity. In: Orthodontics & Craniofacial Research, vol. 2017, no. 20, pp. 140-145, 2017. (Type: Journal Article | Abstract | Links | BibTeX | Tags: Discrepency Index, malocclusion severity, Peer Assessment Rating Index)@article{Liu2017, Objectives: To assess the validity of the American Board of Orthodontics Discrepancy Index (ABO-DI) and Peer Assessment Rating (PAR) Index in evaluating malocclusion severity in Chinese orthodontic patients.Setting and Sample Population: A stratified random sample of 120 orthodontic patients based on Angle classification was collected from six university orthodontic centres. Material and Methods: Sixty-nine orthodontists rated malocclusion severity on a five-point scale by assessing a full set of pre-treatment records for each case and listed reasons for their decision. Their judgement was then compared with ABO-DI and PAR scores determined by three calibrated examiners. Results: Excellent interexaminer reliability of clinician judgement, ABO-DI and PAR index was demonstrated by the Intraclass Correlation Coefficient (rho= 0.995, 0.990 and 0.964, respectively). Both the ABO-DI and US-PAR index showed good correlation with clinician judgement (r=.700 and r=.707, respectively). There was variability among the different Angle classifications: the ABO-DI showed the highest correlation with clinician judgement in Class II patients (r=.780), whereas the US-PAR index showed the highest correlation with clinician judgement in Class III patients (r=.710). Both indices demonstrated the lowest correlations with clinician judgement in Class I patients. Conclusion: With strong interexaminer agreement, the panel consensus was used for validating the ABO-DI and US-PAR index for malocclusion severity. Overall, the ABO-DI and US-PAR index were reliable for measuring malocclusion severity with significantly variable weightings for different Angle classifications. Further modification of the indices for different Angle classification may be indicated. |
Oh, H; Baumrind, S; Dugoni, S; Boero, R; Aubert, M; Boyd, R: A retrospective study of Class II mixed-dentition treatment. . In: Angle Orthodontist, vol. 87, no. 1, pp. 56-67, 2017. (Type: Journal Article | Abstract | Links | BibTeX | Tags: AAOF, clinical orthodontist, Cone-beam computed tomography, Cranial base, craniofacial, Discrepency Index, Growth, hyperdivergent, malocclusion severity, Mandibular fixed retainer, Mandibular remodeling, mapping, technique, vertical control, x-ray)@article{Oh2017, To consider the effectiveness of early treatment using one mixed-dentition approach to the correction of moderate and severe Class II malocclusions. |