Dental quackery in India: an insight on malpractices and measures to tackle them

Jain, Anuj

doi:10.1038/s41415-019-0014-3

Cited by 10 publications

(9 citation statements)

References 7 publications

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“…Further iterations of such an implementation can also help licensed practitioners quickly screen the quality of work performed by quacks. who are known to administer questionable treatment to patients in poorer communities across developing country [11]. Previous reports of automated prediction of failed endodontic obturation were documented from patient history and symptoms upon follow-ups using logistic regression (logR), random forests (RF), gradient boosting machine (GBM), and extreme gradient boosting (XGB) for machine-learning driven predictive modeling [25].…”

Section: Discussionmentioning

confidence: 99%

Experimental validation of computer-vision methods for the successful detection of endodontic treatment obturation and progression from noisy radiographs

et al. 2023

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Purpose (1) To evaluate the effects of denoising and data balancing on deep learning to detect endodontic treatment outcomes from radiographs. (2) To develop and train a deep-learning model and classifier to predict obturation quality from radiomics. Methods The study conformed to the STARD 2015 and MI-CLAIMS 2021 guidelines. 250 deidentified dental radiographs were collected and augmented to produce 2226 images. The dataset was classified according to endodontic treatment outcomes following a set of customized criteria. The dataset was denoised and balanced, and processed with YOLOv5s, YOLOv5x, and YOLOv7 models of real-time deep-learning computer vision. Diagnostic test parameters such as sensitivity (Sn), specificity (Sp), accuracy (Ac), precision, recall, mean average precision (mAP), and confidence were evaluated. Results Overall accuracy for all the deep-learning models was above 85%. Imbalanced datasets with noise removal led to YOLOv5x’s prediction accuracy to drop to 72%, while balancing and noise removal led to all three models performing at over 95% accuracy. mAP saw an improvement from 52 to 92% following balancing and denoising. Conclusion The current study of computer vision applied to radiomic datasets successfully classified endodontic treatment obturation and mishaps according to a custom progressive classification system and serves as a foundation to larger research on the subject matter.

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Section: Discussionmentioning

confidence: 99%

Experimental validation of computer-vision methods for the successful detection of endodontic treatment obturation and progression from noisy radiographs

et al. 2023

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“…The U.S. Congress determined quackery to be massively dangerous consumer fraud against older adults [1]. All medical fields affect quackery, such as dentistry [20]- [22], homeopathy, and even dermatology [23]. The word denturism is used in some countries, and it seems to be a questionable practice [24] because they are practically outside their legal qualifications [21].…”

Section: Related Workmentioning

confidence: 99%

QuackFinder: A Probabilistic Approach

Bukhari

Saleem

Zafar

et al. 2022

IJIST

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Quackery is profoundly rooted in rural areas, , but cities are also considerably affected. Countries, whether developed or developing, are experiencing this curse. Quackery is one of the primary reasons for the recent AIDS epidemic among children in Pakistan. In this research, we have conducted two separate surveys to study the causes of quackery. The sample sizes for the public and physicians were 157 and 58, respectively. The first questionnaire was handed to the respondents based in Pakistan to reveal the reasons behind the quackery and its widespread existence. The second questionnaire was designed to examine physicians' perceptions of quackery. The data were analyzed and we physicians having permit granted by the PMDC (Pakistan Medical and Dental Council) should be placed in doctor's clinics to help people distinguish between quacks and physicians. According to the conducted survey government may be held accountable behind the spread of quackery whereas lack of awareness from the media and high illiteracy rates are also the lead causes. Moreover, according to doctor’s perspective, awareness campaigns will surely help us to overcome this menace. It is not simple for common people to differentiate a quack from a doctor. To assist the common person, we have created a prototype android app called "Quack Finder"' based on our survey outcomes to predict whether an individual is a quack or a doctor.

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“…The World Health Organization suggested to have New Dental Auxiliaries like dental aid, dental licentiate, and frontier auxiliaries with little training to work in rural remote areas [8]. Sandesh et al and other have suggested [7,9,10]. 1.…”

Section: Suggestion By Whomentioning

confidence: 99%

Quackery in Dentistry—a serious concern

Sowmya¹,

Sushma²,

Anupama³

2020

IJCRD

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Quackery/street dentistry in dental profession has been an issue for quite a long time. It emerges when there are deficient quantities of capable and prepared specialists or when their charges seem restrictive to a portion of the population. Inadequately instructed individuals frequently become prey to quacks who perform dental treatment, which is destructive to patients and the quality of life is compromised. The time has come to take measures to stop such exploitative practices.

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Dental quackery in India: an insight on malpractices and measures to tackle them

Cited by 10 publications

References 7 publications

Experimental validation of computer-vision methods for the successful detection of endodontic treatment obturation and progression from noisy radiographs

Experimental validation of computer-vision methods for the successful detection of endodontic treatment obturation and progression from noisy radiographs

QuackFinder: A Probabilistic Approach

Quackery in Dentistry—a serious concern

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