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Related Experiment Video

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Scanning Skeletal Remains for Bone Mineral Density in Forensic Contexts

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Mathematically optimal decisions in forensic age assessment.

Petter Mostad^1,2, Andreas Schmeling³, Fredrik Tamsen⁴

¹Mathematical Sciences, Chalmers University of Technology, Gothenburg, Sweden. mostad@chalmers.se.

International Journal of Legal Medicine

|December 15, 2021

Summary

Forensic age estimation faces uncertainty. This study uses mathematical theory for optimal decisions, suggesting individual prior knowledge improves accuracy, unlike general priors.

Keywords:

Age assessment Bayesian Femur Knee Third molar

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Area of Science:

Forensic Science
Biostatistics
Radiology

Background:

Forensic age estimation relies on indicators like teeth and skeleton, which inherently have uncertainty.
Accurate age prediction remains challenging, necessitating methods for optimal decision-making under uncertainty.

Purpose of the Study:

To apply mathematical theory for statistically optimal decisions in forensic age assessment.
To explore the necessity and application of individual prior probability distributions for age.

Main Methods:

Utilized mathematical theory for statistically optimal decision-making in age assessment.
Developed a framework assuming standardized data collection and prior probability distributions for age.
Applied the theoretical framework to Magnetic Resonance Imaging (MRI) data of distal femur and third molar maturity.

Main Results:

Individual prior distributions for age, selected by caseworkers, are likely necessary for optimal decisions.
Information can be collected over time to enhance the robustness of age assessment procedures.
A weak positive conditional correlation was observed between distal femur and third molar maturity.

Conclusions:

Optimal forensic age estimation requires statistically sound decision-making under uncertainty.
Individualized prior knowledge, rather than a common prior, is crucial for improving age assessment accuracy.
The proposed theoretical framework provides a robust approach for forensic age estimation using maturity indicators.