ReviewFrontiers in microbiology2022
Advances in artificial intelligence-based microbiome for PMI estimation.
Review in Frontiers in microbiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
15 citing papers in PubMed.
- Application of artificial intelligence in the determination of the postmortem interval: Systematic review of the literature and metaanalysis.Forensic science, medicine, and pathology · 2026Review
- Application of artificial intelligence in the determination of the postmortem interval: Systematic review of the literature and metaanalysis.Forensic science, medicine, and pathology · 2026Review
- Artificial intelligence based on forensic medical databases: construction, application, and prospects.Forensic science, medicine, and pathology · 2026Review
- Estimating the Post-Mortem Interval Under Extreme Heat Environments: A Climate-Adaptive Case Series Based on Artificial Intelligence-Supported Diagnostics.Diagnostics (Basel, Switzerland) · 2026Article
- Current Understanding and Future Research Direction for Estimating the Postmortem Interval: A Systematic Review.Diagnostics (Basel, Switzerland) · 2025Review
- Unveiling the Forensic Potential of Oral and Nasal Microbiota in Post-Mortem Interval Estimation.International journal of molecular sciences · 2025Article
- Exploring the Post Mortem Interval (PMI) Estimation Model by circRNAInternational journal of molecular sciences · 2025Article
- RedefiningFrontiers in microbiology · 2025Review
- Multimodal Approaches Based on Microbial Data for Accurate Postmortem Interval Estimation.Microorganisms · 2024Review
- Estimating postmortem interval based on oral microbial community succession in rat cadavers.Heliyon · 2024Article
- ChatGPT in forensic sciences: a new Pandora's box with advantages and challenges to pay attention.Forensic sciences research · 2023Article
- Changes in Microbial Communities Using Pigs as a Model for Postmortem Interval Estimation.Microorganisms · 2023Article
- The Future Is Now: Unraveling the Expanding Potential of Human (Necro)Microbiome in Forensic Investigations.Microorganisms · 2023Review
- Enhancing the Evidence with Algorithms: How Artificial Intelligence Is Transforming Forensic Medicine.Diagnostics (Basel, Switzerland) · 2023Review
- Advances in machine learning-based bacteria analysis for forensic identification: identity, ethnicity, and site of occurrence.Frontiers in microbiology · 2023Review
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Postmortem interval (PMI) estimation has always been a major challenge in forensic science. Conventional methods for predicting PMI are based on postmortem phenomena, metabolite or biochemical changes, and insect succession. Because postmortem microbial succession follows a certain temporal regularity, the microbiome has been shown to be a potentially effective tool for PMI estimation in the last decade. Recently, artificial intelligence (AI) technologies shed new lights on forensic medicine through analyzing big data, establishing prediction models, assisting in decision-making, etc. With the application of next-generation sequencing (NGS) and AI techniques, it is possible for forensic practitioners to improve the dataset of microbial communities and obtain detailed information on the inventory of specific ecosystems, quantifications of community diversity, descriptions of their ecological function, and even their application in legal medicine. This review describes the postmortem succession of the microbiome in cadavers and their surroundings, and summarizes the application, advantages, problems, and future strategies of AI-based microbiome analysis for PMI estimation.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.