Age estimation at death in individuals over 50 using CT images: An innovative anthropological approach

The aim of the present work is to develop a novel method for predicting age in individuals over 50 years old, utilizing regression models.

The conducted study is of an analytical cross-sectional nature, involving a sample of 44 young subjects and 107 elderly subjects. The necessary data for this research were extracted from "The New Mexico Decedent Image Database." Based on the phenomenon of height shrinkage with age, we created models for young subjects and applied them to elderly subjects, allowing us to extract the variables.

We obtained highly encouraging results with an R² of 0.73, a mean absolute error of 3.94, and stable cross-validation. We used a Student's t-test, which demonstrated no significant difference between predicted and actual values (p-value >0.05). We also conducted a learning curve analysis and examined residuals against predicted values. This suggests that the forecasts are accurate, with no significant bias in predictions.

This work has allowed us to conclude that it is possible to reliably estimate the age of subjects over 50, taking into account age-related physiological and pathological changes.