RT Journal Article
T1 Translational Applications of Artificial Intelligence and Machine Learning for Diagnostic Pathology in Lymphoid Neoplasms: A Comprehensive and Evolutive Analysis
A1 Moran-Sanchez, Julia
A1 Santisteban-Espejo, Antonio
A1 Martin-Piedra, Miguel Angel
A1 Perez-Requena, Jose
A1 Garcia-Rojo, Marcial
K1 Artificial intelligence
K1 Hematopathology
K1 Lymphoid neoplasms
K1 Digital image analysis
K1 Machine learning
K1 Inteligencia artificial
K1 Linfoma no Hodgkin
K1 Procesamiento de imagen asistido por computador
K1 Aprendizaje automático
AB Genomic analysis and digitalization of medical records have led to a big data scenario within hematopathology. Artificial intelligence and machine learning tools are increasingly used to integrate clinical, histopathological, and genomic data in lymphoid neoplasms. In this study, we identified global trends, cognitive, and social framework of this field from 1990 to 2020. Metadata were obtained from the Clarivate Analytics Web of Science database in January 2021. A total of 525 documents were assessed by document type, research areas, source titles, organizations, and countries. SciMAT and VOSviewer package were used to perform scientific mapping analysis. Geographical distribution showed the USA and People's Republic of China as the most productive countries, reporting up to 190 (36.19%) of all documents. A third-degree polynomic equation predicts that future global production in this area will be three-fold the current number, near 2031. Thematically, current research is focused on the integration of digital image analysis and genomic sequencing in Non-Hodgkin lymphomas, prediction of chemotherapy response and validation of new prognostic models. These findings can serve pathology departments to depict future clinical and research avenues, but also, public institutions and administrations to promote synergies and optimize funding allocation.
PB MDPI
YR 2021
FD 2021-05-25
LK http://hdl.handle.net/10668/4224
UL http://hdl.handle.net/10668/4224
LA en
NO Moran-Sanchez J, Santisteban-Espejo A, Martin-Piedra MA, Perez-Requena J, Garcia-Rojo M. Translational Applications of Artificial Intelligence and Machine Learning for Diagnostic Pathology in Lymphoid Neoplasms: A Comprehensive and Evolutive Analysis. Biomolecules. 2021 May 25;11(6):793.
DS RISalud
RD Apr 18, 2025