Investigating the new orientation of wound age estimation in forensic medicine based on biological omics data combined with artificial intelligence algorithms

Investigating the new orientation of wound age estimation in forensic medicine based on biological omics data combined with artificial intelligence algorithms

연구 분야: Analysis

학회: CAIH2020: Proceedings of the 2020 Conference on Artificial Intelligence and Healthcare

The studies on wound age estimation in forensic medicine has been made gratifying progress in building mathematical models based on multiple indexes at various levels. However, the subjectivity of the selection of biological indicators, poor practical operability and single analysis method impact the accuracy of the wound time estimation. As the biomedical sciences are moving towards multidisciplinary fields and large-scale omics big data, artificial intelligence technologies and network informatics for generating and processing large biological data sets are promoting key changes in biomedical scientific research. In this article, we raised the new application of multiple data sets combined with artificial intelligence algorithms on wound age estimation in forensic based on our newest achievements which based on the transcriptomics data. This indicated that biomedicine, forensic medicine and computer science will be cross-disciplined to expound the feasibility of combining multiple omics technologies and artificial intelligence algorithms in wound age estimation on forensic, so as to explore the new direction of the wound age estimation in forensic research.