Advances in artificial intelligence-based microbiome for PMI estimation

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.

Enhancing the Evidence with Algorithms: How Artificial Intelligence Is Transforming Forensic Medicine

“…Zou Y et al state that AI technology is in full development for data processing and is already being used by some researchers as a conventional method for PMI estimation [ 27 ]. By applying next-generation sequencing (NGS) and AI techniques, the forensic pathologist can enhance 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 forensic medicine and pathology through post-mortem sequencing of the cadaveric microbiome [ 28 ].…”

Advances in machine learning-based bacteria analysis for forensic identification: identity, ethnicity, and site of occurrence

“…While the succession of microbial communities is generally consistent across various soil types, the microbial community in the environment influences the decomposition processes of the cadaveric microbial community. As decomposing carcasses release a range of substances, including fatty tissues, volatile fatty acids, organic acids, organic nitrogen and specific anaerobic bacteria, into the soil ( Wang et al, 2022 ), forensic identification based on microbial communities becomes feasible. Nevertheless, microbial communities alone are susceptible to external factors that limit their utility in forensic identification-a challenge that artificial intelligence (AI) may address by constructing effective assessment models.…”

Changes in Microbial Communities Using Pigs as a Model for Postmortem Interval Estimation

“…It is widely recognized that microbiota can be utilized for PMI estimation [6][7][8][9][10][11][12][13][14]. During the fresh stage, cellular macromolecules are released shortly after death, and the microbiota play a crucial role in breaking down these macromolecules into simpler compounds [15].…”

“…Numerous researchers have conducted comprehensive investigations into microbial succession, focusing predominantly on murine models [8,13,[19][20][21][22][23][24][25], specifically rats and mice [2,26]. Metcalf et al found a "microbial clock" with the capacity to estimate the PMI with a margin of error approximating ±3 days [2], while the experiment was carried out under rigorously controlled circumstances, utilizing experimental mouse models, thus necessitating judicious interpretation when extrapolating these findings to authentic, realworld scenarios [27].…”