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Treffer: Technical note: Automated data extraction from autopsy reports using a custom Python script.

Title:
Technical note: Automated data extraction from autopsy reports using a custom Python script.
Authors:
Busch JR; Section of Forensic Pathology, Department of Forensic Medicine, University of Copenhagen, Frederik V's Vej 11, Copenhagen 2100, Denmark. Electronic address: johannes.busch@sund.ku.dk., Wingren CJ; Section of Forensic Pathology, Department of Forensic Medicine, University of Copenhagen, Frederik V's Vej 11, Copenhagen 2100, Denmark.
Source:
Forensic science international [Forensic Sci Int] 2026 Jan; Vol. 379, pp. 112756. Date of Electronic Publication: 2025 Nov 26.
Publication Type:
Journal Article
Language:
English
Journal Info:
Publisher: Elsevier Science Ireland Country of Publication: Ireland NLM ID: 7902034 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1872-6283 (Electronic) Linking ISSN: 03790738 NLM ISO Abbreviation: Forensic Sci Int Subsets: MEDLINE
Imprint Name(s):
Publication: Limerick : Elsevier Science Ireland
Original Publication: Lausanne, Elsevier Sequoia.
MeSH Terms:
Software* , Programming Languages* , Information Storage and Retrieval*/methods, Humans ; Autopsy ; Cause of Death ; Male ; Organ Size
Contributed Indexing:
Keywords: Automation; Autopsy; Data extraction; Forensic pathology; Records
Entry Date(s):
Date Created: 20251130 Date Completed: 20260108 Latest Revision: 20260108
Update Code:
20260109
DOI:
10.1016/j.forsciint.2025.112756
PMID:
41319600
Database:
MEDLINE

Weitere Informationen

Evidence-based forensic research necessitates the creation of large and valid datasets. However, in our experience many departments face a challenge in how to extract this data from electronically archived records. This technical note describes a custom script created in the Python programming language. The program can extract data on decedent sex, age, body height, body weight, organ weight, organ dimensions, degree of putrefaction, listed cause of death, medical history and scene description from approximately 23,000 records in under two hours. Validity for many of these data are around 97-99 %. The program can be modified to extract any type of information. Data that are structured uniformly in the records result in higher data validity. Compared with manual extraction of data, automated extraction provide several benefits, including speed, accuracy, and flexibility.
(Copyright © 2025 The Authors. Published by Elsevier B.V. All rights reserved.)

Declaration of Competing Interest The authors have no competing interests to declare.