Natural Language Processing to extract SNOMED-CT codes from pathological reports-Reference-Cited by-同舟云学术

Natural Language Processing to extract SNOMED-CT codes from pathological reports

Published:2023-12 Issue:6 Volume:115 Page:318-324
ISSN:1591-951X
Container-title:Pathologica
language:
Short-container-title:Pathologica

Author:

Cazzaniga Giorgio,Eccher Albino,Munari Enrico,Marletta Stefano,Bonoldi Emanuela,Della Mea Vincenzo,Cadei Moris,Sbaraglia Marta,Guerriero Angela,Dei Tos Angelo Paolo,Pagni Fabio,L’Imperio Vincenzo

Publisher

Siapec Servizi Srl

Reference36 articles.

1. Caputo A, L’Imperio V, Merolla F, et al. The slow-paced digital evolution of pathology: lights and shadows from a multifaceted board. Pathologica 2023;115:127-136. https://doi.org/10.32074/1591-951X-868

2. Cazzaniga G, Rossi M, Eccher A, et al. Time for a full digital approach in nephropathology: a systematic review of current artificial intelligence applications and future directions. J Nephrol Published online September 28, 2023. https://doi.org/10.1007/s40620-023-01775-w

3. Cazzaniga G, Bolognesi MM, Stefania MD, et al. Congo Red Staining in Digital Pathology: The Streamlined Pipeline for Amyloid Detection Through Congo Red Fluorescence Digital Analysis. Lab Invest 2023;103:100243. https://doi.org/10.1016/j.labinv.2023.100243

4. L’Imperio V, Wulczyn E, Plass M, et al. Pathologist Validation of a Machine Learning-Derived Feature for Colon Cancer Risk Stratification. JAMA Netw Open 2023;6:e2254891. https://doi.org/10.1001/jamanetworkopen.2022.54891

5. Marletta S, L’Imperio V, Eccher A, et al. Artificial intelligence-based tools applied to pathological diagnosis of microbiological diseases. Pathol Res Pract 2023;243:154362. https://doi.org/10.1016/j.prp.2023.154362.

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