| Autor: |
MA Ji-wei, HUANG Ping, ZHANG Ji, YU Hai-xing, CAO Yong-jie, YANG Xiao-tong, XIONG Jian, ZHANG Huai-han, CANG Yong, SHI Ge-fei, CHEN Li-qin |
| Jazyk: |
čínština |
| Rok vydání: |
2024 |
| Předmět: |
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| Zdroj: |
Fayixue Zazhi, Vol 40, Iss 3, Pp 245-253 (2024) |
| Druh dokumentu: |
article |
| ISSN: |
1004-5619 |
| DOI: |
10.12116/j.issn.1004-5619.2023.430803 |
| Popis: |
ObjectiveTo describe the current state of research and future research hotspots through a metrological analysis of the literature in the field of forensic anthropological remains identification research.MethodsThe data retrieved and extracted from the Web of Science Core Collection （WoSCC）， the core database of the Web of Science information service platform （hereinafter referred to as “WoS”）， was used to analyze the trends and topic changes in research on forensic identification of human remains from 1991 to 2022. Network visualisation of publication trends, countries （regions）, institutions, authors and topics related to the identification of remains in forensic anthropology was analysed using python 3.9.2 and Gephi 0.10.ResultsA total of 873 papers written in English in the field of forensic anthropological remains identification research were obtained. The journal with the largest number of publications was Forensic Science International （164 articles）. The country （region） with the largest number of published papers was China （90 articles）. Katholieke Univ Leuven （Netherlands， 21 articles） was the institution with the largest number of publications. Topic analysis revealed that the focus of forensic anthropological remains identification research was sex estimation and age estimation, and the most commonly studied remains were teeth.ConclusionThe volume of publications in the field of forensic anthropological remains identification research has a distinct phasing. However, the scope of both international and domestic collaborations remains limited. Traditionally, human remains identification has primarily relied on key areas such as the pelvis, skull, and teeth. Looking ahead, future research will likely focus on the more accurate and efficient identification of multiple skeletal remains through the use of machine learning and deep learning techniques. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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