Madhur Upadhyay

Dr. Madhur Upadhyay

Division of Orthodontics, Department of Craniofacial Sciences, Farmington Avenue, Farmington, MI, USA
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Research Focus & Metrics

Academic Career Length

21Years (2006-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 February 2022 in Journal of the World Federation of Orthodontists
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Journal Article
Closed access
Madhur UpadhyayMadhur Upadhyay
Madhur Upadhyay
SASarah Abu Arqub
Sarah Abu Arqub

1 July 2008 in American Journal of Orthodontics and Dentofacial Orthopedics
Verified
Journal Article
Closed access
Madhur UpadhyayMadhur Upadhyay
Madhur Upadhyay
SYSumit Yadav
Sumit Yadav
KNK. Nagaraj
K. Nagaraj
SPSameer Patil
Sameer Patil

1 December 2008 in American Journal of Orthodontics and Dentofacial Orthopedics
Verified
Journal Article
Closed access
Madhur UpadhyayMadhur Upadhyay
Madhur Upadhyay
SYSumit Yadav
Sumit Yadav
SPSameer Patil
Sameer Patil

1 February 2018 in American Journal of Orthodontics and Dentofacial Orthopedics
Verified
Journal Article
Closed access
ACAditya Chhibber
Aditya Chhibber
SASachin Agarwal
Sachin Agarwal
SYSumit Yadav
Sumit Yadav
CKChia-Ling Kuo
Chia-Ling Kuo
Madhur UpadhyayMadhur Upadhyay
Madhur Upadhyay

12 June 2020 in Bioengineering
Verified
Journal Article
Open access
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Yasir SuhailYasir Suhail
Yasir Suhail
Madhur UpadhyayMadhur Upadhyay
Madhur Upadhyay
ACAditya Chhibber
Aditya Chhibber
KKKshitiz Kshitiz
Kshitiz Kshitiz
Extraction of teeth is an important treatment decision in orthodontic practice. An expert system that is able to arrive at suitable treatment decisions can be valuable to clinicians for verifying treatment plans, minimizing human error, training orthodontists, and improving reliability. In this work, we train a number of machine learning models for this prediction task using data for 287 patients, evaluated independently by five different orthodontists. We demonstrate why ensemble methods are particularly suited for this task. We evaluate the performance of the machine learning models and interpret the training behavior. We show that the results for our model are close to the level of agreement between different orthodontists.

1 March 2009 in The Angle Orthodontist
Verified
Journal Article
Closed access
Madhur UpadhyayMadhur Upadhyay
Madhur Upadhyay
SYSumit Yadav
Sumit Yadav
KNK. Nagaraj
K. Nagaraj
RNRavindra Nanda
Ravindra Nanda
Objective: To examine the skeletal, dental, and soft tissue treatment effects of retraction of maxillary anterior teeth with mini-implant anchorage in nongrowing Class II division 1 female patients. Materials and Methods: Twenty-three patients (overjet ≥7 mm) were selected on the basis of predefined selection criteria. Treatment mechanics consisted of retraction of anterior teeth by placing mini-implants in the interdental bone between the roots of the maxillary first molar and second premolar. A force of 150 g was applied, bilaterally. Treatment effects were analyzed by taking lateral cephalograms and study casts at T1 (before initiation of retraction) and at T2 (after complete space closure). Results: The upper anterior teeth showed significant retraction (5.18 ± 2.74 mm) and intrusion (1.32 ± 1.08 mm). The upper first molar also showed some distal movement and intrusion, but this was not significant (P > .05). The upper and lower lips were retracted by 2.41 mm and 2.73 mm, respectively, and the convexity angle reduced by over 2° (P < .001). Conclusion: Mini-implants provided absolute anchorage to bring about significant dental and soft tissue changes in moderate to severe Class II division 1 patients and can be considered as possible alternatives to orthognathic surgery in select cases. (Angle Orthod. 2009:79; )