BioAlder: a tool for assessing chronological age based on two radiological methods.

Area of Science:

• Forensic Anthropology
• Developmental Biology
• Biometrics

Background:

• Accurate age estimation is crucial in forensic and clinical settings.
• Existing methods like Greulich and Pyle (hand) and Demirjian's (tooth) grading have limitations.
• Integrating multiple assessment systems can potentially improve age prediction accuracy.

Purpose of the Study:

• To develop and validate BioAlder, a novel age prediction model.
• To combine hand and third molar tooth age assessment systems.
• To address data format and age mimicry biases in age estimation.

Main Methods:

• Created the BioAlder tool integrating Greulich and Pyle (hand) and Demirjian's (tooth) grading systems.
• Compiled data from 17,151 individuals globally.
• Tested the model and its independency assumption on a separate dataset of 254 individuals from Lebanon.

Main Results:

• The BioAlder model integrates hand and tooth age assessments, bypassing group-wise data format and age mimicry biases.
• Prediction intervals from BioAlder generally covered data points in the test set.
• Observed outliers and identified at least a weak dependency between the hand and tooth grading systems.

Conclusions:

• BioAlder provides a unified approach to age prediction using skeletal and dental indicators.
• The model demonstrates potential for improved age estimation by combining different assessment modalities.
• Further research is warranted to explore the dependency between hand and tooth age assessments for refined predictions.