Automated Author Profile

Ridoy, Ridoy kumar Das

American International University Bangladesh

Current S-Index

0.8

Sum of Dataset Indices for all datasets

Average Dataset Index per Dataset

0.4

Average Dataset Index per dataset

Total Datasets

2

Total datasets for this author

Average FAIR Score

65.4%

Average FAIR Score per dataset

Total Citations

0

Total citations to the author's datasets

Total Mentions

0

Total mentions of the author's datasets

S-Index Interpretation

S-Index Over Time

Cumulative Citations Over Time

Cumulative Mentions Over Time

Datasets

A Deep Learning Framework for Automated Detection and Classification of Four Common Dental Diseases Using Dental Radiographs

Dataset Description:This dataset consists of Orthopantomogram (OPG) dental X-ray images collected from the Global Orthopedic General Hospital & Diagnostic Center in Bangladesh. It is designed for object detection, disease classification, image analysis, and segmentation. The dataset is organized into two main folders: Object Detection Dataset and Classification Dataset.The Object Detection Dataset folder contains 4000 original and 10,000 augmented images with labeled annotations.The Classification Dataset folder consists of separate files for each dental condition class.Images are stored in JPG format, while labels are in JSON format. The dataset is divided into training (70%), validation (20%), and testing (10%) sets.Dataset collection:• Source: Global Orthopedic General Hospital and Diagnostic Center.• Capture Method: Hard drive.• Anonymization : All information was carefully removed to protect privacy and confidentiality.• Informed Consent: Consent was knowingly given by each patient in compliance with dental ethics.Variables: Cavities:2500 Damage/Broken :2500 Infection: 2500 Wisdom teeth: 2500

Authors

  • FESANI, AL ;
  • Chowdhury, Shorbani ;
  • Haidar, Jamil ;
  • Ridoy, Ridoy kumar Das ;
  • Biswas, Rahul ;
  • Rahman, Mahfujur ;
  • Dey, Noboranjan
0 Citations0 Mentions65% FAIR0.4 Dataset Index
10.17632/wxv6h9p39g2025

A Deep Learning Framework for Automated Detection and Classification of Four Common Dental Diseases Using Dental Radiographs

Dataset Description:This dataset consists of Orthopantomogram (OPG) dental X-ray images collected from the Global Orthopedic General Hospital & Diagnostic Center in Bangladesh. It is designed for object detection, disease classification, image analysis, and segmentation. The dataset is organized into two main folders: Object Detection Dataset and Classification Dataset.The Object Detection Dataset folder contains 4000 original and 10,000 augmented images with labeled annotations.The Classification Dataset folder consists of separate files for each dental condition class.Images are stored in JPG format, while labels are in JSON format. The dataset is divided into training (70%), validation (20%), and testing (10%) sets.Dataset collection:• Source: Global Orthopedic General Hospital and Diagnostic Center.• Capture Method: Hard drive.• Anonymization : All information was carefully removed to protect privacy and confidentiality.• Informed Consent: Consent was knowingly given by each patient in compliance with dental ethics.Variables: Cavities:2500 Damage/Broken :2500 Infection: 2500 Wisdom teeth: 2500

Authors

  • FESANI, AL ;
  • Chowdhury, Shorbani ;
  • Haidar, Jamil ;
  • Ridoy, Ridoy kumar Das ;
  • Biswas, Rahul ;
  • Rahman, Mahfujur ;
  • Dey, Noboranjan
0 Citations0 Mentions65% FAIR0.4 Dataset Index
10.17632/wxv6h9p39g.12025