Your browser doesn't support javascript.
loading
Mostrar: 20 | 50 | 100
Resultados 1 - 1 de 1
Filtrar
Más filtros

Bases de datos
Tipo del documento
Asunto de la revista
País de afiliación
Intervalo de año de publicación
1.
Fa Yi Xue Za Zhi ; 40(3): 245-253, 2024 Jun 25.
Artículo en Inglés, Zh | MEDLINE | ID: mdl-39166305

RESUMEN

OBJECTIVES: To 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. METHODS: The 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. RESULTS: A 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. CONCLUSIONS: The 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.


Asunto(s)
Bibliometría , Restos Mortales , Antropología Forense , Humanos , Antropología Forense/métodos , Publicaciones/estadística & datos numéricos
SELECCIÓN DE REFERENCIAS
DETALLE DE LA BÚSQUEDA