Visual Diagnostics of Dental Caries through Deep Learning of Non-Standardised Photographs Using a Hybrid YOLO Ensemble and Transfer Learning Model.

Journal: International journal of environmental research and public health
Published Date: Mar 31, 2023

Abstract

BACKGROUND: Access to oral healthcare is not uniform globally, particularly in rural areas with limited resources, which limits the potential of automated diagnostics and advanced tele-dentistry applications. The use of digital caries detection and progression monitoring through photographic communication, is influenced by multiple variables that are difficult to standardize in such settings. The objective of this study was to develop a novel and cost-effective virtual computer vision AI system to predict dental cavitations from non-standardised photographs with reasonable clinical accuracy.

Authors

  • Abu Tareq
    Department of Electrical and Computer Engineering, North South University, Dhaka 1229, Bangladesh.
  • Mohammad Imtiaz Faisal
    Department of Electrical and Computer Engineering, North South University, Dhaka 1229, Bangladesh.
  • Md Shahidul Islam
    Department of Biochemistry, School of Life Sciences, University of KwaZulu- Natal (Westville Campus), Durban 4000, Durban, South Africa.
  • Nafisa Shamim Rafa
    Department of Electrical and Computer Engineering, North South University, Dhaka 1229, Bangladesh.
  • Tashin Chowdhury
    Department of Electrical and Computer Engineering, North South University, Dhaka 1229, Bangladesh.
  • Saif Ahmed
    Lecturer, Department of Electrical and Computer Engineering, North South University, Dhaka, Bangladesh.
  • Taseef Hasan Farook
    Maxillofacial Prosthetic Service, Prosthodontic Unit, School of Dental Sciences, UniversitiSains Malaysia, Health Campus, Kelantan 16150, Malaysia.
  • Nabeel Mohammed
    Apurba NSU R&D Lab, Department of Electrical and Computer Engineering North South University, Dhaka, Bangladesh.
  • James Dudley
    Associate Professor, Adelaide Dental School, The University of Adelaide, South Australia, Australia.

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