Sharma, Himani (2024) Enhancing the Early Detection of Dental problem through Transfer Learning Techniques in Dental Radiography. Masters thesis, Dublin, National College of Ireland.
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Abstract
The poorest showing is represented by the sphere of public health with its focus on the most vital human health procedures and phenomena one’s teeth. Such measurements allow dental panoramic radiography to be widely accepted among dentists in diagnosing and researching such diseases and with general exposure of the whole oral area use protective measures of low radiation dose and radiation time. To detect these matters, dentists have varieties of radiography like the panoramic views which do not take much time and have a low degree of radiation and perhaps, provide the visualize of the whole area in the mouth. It may take several hours and the whole process may tend to be tiresome especially when the veterinarian is interpreting the radiographs. Modern trends have allowed the dentists to complete the analyses in a shorter time with the support of various forms of Artificial Intelligence. It is rather sad today to such a group of people who require these services to part with an enormous amount of money to be treated by a doctor or maybe even get an x-ray. Large movies are when the malformations cannot be touched with the help of fingers In such a way, big movies are utilized by doctors. It assists in the management of the modern diseases such as caries, deep caries, impacted teeth and periapical lesions; hence development of cheap dental health care services.
Item Type: | Thesis (Masters) |
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Supervisors: | Name Email Milosavljevic, Vladimir UNSPECIFIED |
Uncontrolled Keywords: | Caries Detection; Impacted Teeth; Periapical Lesions; Affordable Dental Healthcare |
Subjects: | Q Science > QA Mathematics > Electronic computers. Computer science T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science R Medicine > RA Public aspects of medicine > RA0421 Public health. Hygiene. Preventive Medicine R Medicine > RK Dentistry Q Science > Q Science (General) > Self-organizing systems. Conscious automata > Machine learning |
Divisions: | School of Computing > Master of Science in Data Analytics |
Depositing User: | Ciara O'Brien |
Date Deposited: | 25 Aug 2025 11:11 |
Last Modified: | 25 Aug 2025 11:11 |
URI: | https://norma.ncirl.ie/id/eprint/8626 |
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