Classification and detection of dental images using meta-learning.
| Autor: | Yadalam PK; Department of Periodontics, Saveetha Dental College and Hospital, Saveetha Institute of Medical and Technical Sciences, Saveetha University, Chennai 600077, Tamil Nadu, India., Anegundi RV; Department of Periodontics, Saveetha Dental College and Hospital, Saveetha Institute of Medical and Technical Sciences, Saveetha University, Chennai 600077, Tamil Nadu, India., Alarcón-Sánchez MA; South Pacific Dental Institute, Chilpancingo de los Bravo 39022, Guerrero, Mexico., Heboyan A; Department of Prosthodontics, Faculty of Stomatology, Yerevan State Medical University after Mkhitar Heratsi, Yerevan 0025, Armenia. heboyan.artak@gmail.com. |
|---|---|
| Jazyk: | angličtina |
| Zdroj: | World journal of clinical cases [World J Clin Cases] 2024 Nov 16; Vol. 12 (32), pp. 6559-6562. |
| DOI: | 10.12998/wjcc.v12.i32.6559 |
| Abstrakt: | Meta-learning of dental X-rays is a machine learning technique that can be used to train models to perform new tasks quickly and with minimal input. Instead of just memorizing a task, this is accomplished through teaching a model how to learn. Algorithms for meta-learning are typically trained on a collection of training problems, each of which has a limited number of labelled instances. Multiple X-ray classification tasks, including the detection of pneumonia, coronavirus disease 2019, and other disorders, have demonstrated the effectiveness of meta-learning. Meta-learning has the benefit of allowing models to be trained on dental X-ray datasets that are too few for more conventional machine learning methods. Due to the high cost and lengthy collection process associated with dental imaging datasets, this is significant for dental X-ray classification jobs. The ability to train models that are more resistant to fresh input is another benefit of meta-learning. Competing Interests: Conflict-of-interest statement: All the authors declare that they have no conflict of interest. (©The Author(s) 2024. Published by Baishideng Publishing Group Inc. All rights reserved.) |
| Databáze: | MEDLINE |
| Externí odkaz: |
|