Use of Advanced Artificial Intelligence in Forensic Medicine

Abstract

Three-dimensional convolutional neural networks (3D CNN) as a type of artificial intelligence (AI) are powerful in image processing and recognition using deep learning to perform generative and descriptive tasks. The advantage of CNN compared to its predecessors is that it automatically detects the important features without any human supervision. 3D CNN are used to extract features in three dimensions where input is a 3D volume or a sequence of 2D pictures e.g., slices in a cone-beam computer tomography scan (CBCT). The main aim of this article was to bridge interdisciplinary cooperation between forensic medical experts and deep learning engineers. With emphasis activating clinical forensic experts in the field with possibly basic knowledge of advanced artificial intelligence techniques with interest in its implementation in their efforts to advance the forensic research further. This paper introduces a novel workflow of 3D CNN analysis of full-head CBCT scans. Authors explore and present 3D CNN method for forensic research design concept in five perspectives: (1) sex determination, (2) biological age estimation, (3) 3D cephalometric landmark annotation, (4) growth vectors prediction, (5) facial soft-tissue estimation from the skull and vice versa. In conclusion, 3D CNN application can be a watershed moment in forensic medicine, leading to unprecedented improvement of forensic analysis workflows based on 3D neural networks.

Raman spectroscopy for postmortem interval estimation of human skeletal remains: A scoping review

“…Through classification techniques, ML can enhance outcome prediction by sorting data into predetermined categories. Both AI and ML are emerging fields with growing applications in forensic medicine [92], including forensic anthropology [93], forensic psychiatry [94], forensic odontology [95], postmortem imaging [96,97], and PMI estimation [98]. AI has been used in various forensic research, including face recognition [99], cybercrimes [100], age inference [101], cause of death analysis [102], and gene and protein profiling [103,104].…”

Mathematical Basics as a Prerequisite to Artificial Intelligence in Forensic Analysis

“…Multimedia forensic utilizes AI techniques which involve convolution neural network. Analysis of forensic image is used to decode the fake information about photographs using machine learning [3], another important application is in medicine for forensic anthropology [4]. To understand such recent research in multimedia, concepts of image sampling, enhancement, convolution and neural network are included in this chapter.…”