Work overview

Section 06 of 06

Supplementary Information

Artificial intelligence in forensic science: a systematic review. Part II: long-range postmortem interval estimation

Valentina Bugelli, Francesco Calabrò, Jessika Camatti, Rossana Cecchi, Marco Di Paolo, and Lorenzo Franceschetti · 2026

Contents

Section 06 of 06

  1. 01Introduction
  2. 02Materials and methods
  3. 03Results
  4. 04Discussion
  5. 05Conclusions
  6. 06Supplementary Information
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Work overview

Section 6 of 6

Supplementary Information

Valentina Bugelli, Francesco Calabrò, Jessika Camatti, Rossana Cecchi, Marco Di Paolo, and Lorenzo Franceschetti · about 1 minutes

Below is the link to the electronic supplementary material.Supplementary Appendix 1: database search strategy.Supplementary Table S1: Risk-of-bias assessment of included studies according to adapted PROBAST/QUADAS-2 criteria for AI-based postmortem interval (PMI) prediction studies.Abbreviations: RoB – Risk of Bias.Supplementary Table S2: Summary of studies included in this systematic review investigating artificial intelligence (AI) approaches for postmortem interval (PMI) estimation. The table reports study characteristics, including first author and year of publication, data modality used for PMI prediction, biological sample type, sample size, artificial intelligence or machine learning model applied, validation strategy, target outcome (continuous PMI estimation or interval classification), and reported model performance metrics.Abbreviations: AI – Artificial Intelligence; ANN – Artificial Neural Network; AUC – Area Under the Receiver Operating Characteristic Curve; CNN – Convolutional Neural Network; FTIR – Fourier Transform Infrared Spectroscopy; GIS – Geographic Information System; MAE – Mean Absolute Error; ML – Machine Learning; NIR – Near-Infrared Spectroscopy; PMCT – Postmortem Computed Tomography; PMI – Postmortem Interval; PMImin – Minimum Postmortem Interval; PLS – Partial Least Squares; R² – Coefficient of Determination; RF – Random Forest; RMSE – Root Mean Square Error; SVR – Support Vector Regression; XGBoost – eXtreme Gradient Boosting.