Cargando…
Age Assessment through Root Lengths of Mandibular Second and Third Permanent Molars Using Machine Learning and Artificial Neural Networks
The present study explores the efficacy of Machine Learning and Artificial Neural Networks in age assessment using the root length of the second and third molar teeth. A dataset of 1000 panoramic radiographs with intact second and third molars ranging from 12 to 25 years was archived. The length of...
Autores principales: | Patil, Vathsala, Saxena, Janhavi, Vineetha, Ravindranath, Paul, Rahul, Shetty, Dasharathraj K., Sharma, Sonali, Smriti, Komal, Singhal, Deepak Kumar, Naik, Nithesh |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9967887/ https://www.ncbi.nlm.nih.gov/pubmed/36826952 http://dx.doi.org/10.3390/jimaging9020033 |
Ejemplares similares
-
The role of data science in healthcare advancements: applications, benefits, and future prospects
por: Subrahmanya, Sri Venkat Gunturi, et al.
Publicado: (2021) -
Quantitative and Qualitative Correlation of Mandibular Lingual Bone with Risk Factors for Third Molar Using Cone Beam Computed Tomography
por: Halder, Mehuli, et al.
Publicado: (2023) -
Use of Artificial Intelligence-based Computer Vision System to Practice Social Distancing in Hospitals to Prevent Transmission of COVID-19
por: Zeeshan Hameed, B. M., et al.
Publicado: (2020) -
Transforming healthcare through a digital revolution: A review of digital healthcare technologies and solutions
por: Naik, Nithesh, et al.
Publicado: (2022) -
Efficacy of Preemptive Dexamethasone versus Methylprednisolone in the Management of Postoperative Discomfort and Pain after Mandibular Third Molar Surgery: A Systematic Review and Meta-Analysis
por: Singh, Anupam, et al.
Publicado: (2023)