Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

The Fossil Record

The Fossil Record

The fossil record documents only a small fraction of all organisms that have ever inhabited Earth. Fossilization is a rare process, and most organisms never become fossils. Moreover, the fossil record only exhibits fossils that have been discovered. Nevertheless, sedimentary rock fossils of long-lived, abundant, hard-bodied organisms dominate the fossil record. These fossils offer valuable information, such as an organism's physical form, behavior, and age. Studying the fossil record helps...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Using Large Language Model Artificial Intelligence to Enhance Clinical Competency Committee Insight.

AEM education and training·2026

Same author

Computer Vision-based Extraction of Structured Data From Scanned Audiograms in the Electronic Health Record.

Otology & neurotology : official publication of the American Otological Society, American Neurotology Society [and] European Academy of Otology and Neurotology·2025

Same author

A comparative approach of machine learning models to predict attrition in a diabetes management program.

PLOS digital health·2025

Same author

Using artificial intelligence to develop a measure of orthopaedic treatment success from clinical notes.

Frontiers in digital health·2025

Same author

Proximity to COVID-19 vaccination sites and vaccine uptake: the role of gender and vaccine distrust.

Frontiers in public health·2025

Same author

Generative propaganda: Evidence of AI's impact from a state-backed disinformation campaign.

PNAS nexus·2025

Search research articles

Related Experiment Video

Updated: Jul 10, 2026

Proximal Cadaveric Femur Preparation for Fracture Strength Testing and Quantitative CT-based Finite Element Analysis

Proximal Cadaveric Femur Preparation for Fracture Strength Testing and Quantitative CT-based Finite Element Analysis

Published on: March 11, 2017

geoFOR: A collaborative forensic taphonomy database for estimating the postmortem interval.

Katherine E Weisensee¹, Cristina I Tica², Madeline M Atwell¹

¹Department of Sociology, Anthropology and Criminal Justice, Clemson University, Clemson, SC, USA.

Forensic Science International

|January 26, 2024

Summary

Accurate postmortem interval (PMI) estimation is improved with geoFOR, a new collaborative tool. This application uses machine learning and environmental data for better time since death predictions in forensic investigations.

Keywords:

Decomposition GIS Machine learning Open science PMI

More Related Videos

Scanning Skeletal Remains for Bone Mineral Density in Forensic Contexts

Scanning Skeletal Remains for Bone Mineral Density in Forensic Contexts

Published on: January 29, 2018

Image Rendering Techniques in Postmortem Computed Tomography: Evaluation of Biological Health and Profile in Stranded Cetaceans

Published on: September 27, 2020

Related Experiment Videos

Last Updated: Jul 10, 2026

Proximal Cadaveric Femur Preparation for Fracture Strength Testing and Quantitative CT-based Finite Element Analysis

Proximal Cadaveric Femur Preparation for Fracture Strength Testing and Quantitative CT-based Finite Element Analysis

Published on: March 11, 2017

Scanning Skeletal Remains for Bone Mineral Density in Forensic Contexts

Scanning Skeletal Remains for Bone Mineral Density in Forensic Contexts

Published on: January 29, 2018

Image Rendering Techniques in Postmortem Computed Tomography: Evaluation of Biological Health and Profile in Stranded Cetaceans

Published on: September 27, 2020

Area of Science:

Forensic Science
Computational Science
Environmental Science

Background:

Accurate postmortem interval (PMI) estimation is a persistent challenge in forensic science.
Existing methods for PMI determination often lack standardization and robust statistical backing.
The need for a collaborative, data-driven approach to improve PMI accuracy is critical.

Purpose of the Study:

To introduce geoFOR, a web-based collaborative application for enhanced PMI prediction.
To standardize forensic taphonomy data collection and environmental data integration.
To leverage machine learning for statistically robust PMI estimations.

Main Methods:

Development of a web-based collaborative application (geoFOR) integrating ArcGIS and machine learning.
Automated collection of environmental data linked to forensic case information.
Utilization of a cross-validating machine learning model for PMI prediction.

Main Results:

The geoFOR machine learning model achieved a R² value of 0.82 for PMI prediction.
The application provides PMI predictions with an 80% confidence interval.
The geoFOR database currently contains 2529 diverse entries from across the U.S.

Conclusions:

geoFOR offers a novel, standardized approach to building a forensically and geographically representative human decomposition dataset.
Mass collaboration and data sharing through geoFOR can significantly improve PMI estimation accuracy.
The geoFOR repository aims to support open science principles, enabling further refinement of PMI models by the forensic research community.