Artificial Intelligence-Driven Structurization of Diagnostic Information in Free-Text Pathology Reports

BACKGROUND: Free-text sections of pathology reports contain the most important information from a diagnostic standpoint. However, this information is largely underutilized for computer-based analytics. The vast majority of NLP-based methods lack a capacity to accurately extract complex diagnostic en...

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Detalles Bibliográficos
Autores principales: Giannaris, Pericles S., Al-Taie, Zainab, Kovalenko, Mikhail, Thanintorn, Nattapon, Kholod, Olha, Innokenteva, Yulia, Coberly, Emily, Frazier, Shellaine, Laziuk, Katsiarina, Popescu, Mihail, Shyu, Chi-Ren, Xu, Dong, Hammer, Richard D., Shin, Dmitriy
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Wolters Kluwer - Medknow 2020
Materias:
Original Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7045509/
https://www.ncbi.nlm.nih.gov/pubmed/32166042
http://dx.doi.org/10.4103/jpi.jpi_30_19

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7045509/
https://www.ncbi.nlm.nih.gov/pubmed/32166042
http://dx.doi.org/10.4103/jpi.jpi_30_19

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