The More, the Better? Modalities of Metastatic Status Extraction on Free Medical Reports Based on Natural Language Processing-Reference-Cited by-同舟云学术

The More, the Better? Modalities of Metastatic Status Extraction on Free Medical Reports Based on Natural Language Processing

Published:2024-08 Issue:8 Volume: Page:
ISSN:2473-4276
Container-title:JCO Clinical Cancer Informatics
language:en
Short-container-title:JCO Clin Cancer Inform

Author:

Kempf Emmanuelle¹^ORCID,Priou Sonia¹,Cohen Ariel¹^ORCID,Redjdal Akram¹^ORCID,Guével Etienne¹^ORCID,Tannier Xavier¹,

Affiliation:

1. Emmanuelle Kempf, MD, PhD, Sorbonne Université, Inserm, Université Sorbonne Paris-Nord, LIMICS, Paris, France, Department of Medical Oncology, Assistance Publique Hôpitaux de Paris, Henri Mondor Teaching Hospital, Paris, France; Sonia Priou, MSc, Université Paris Saclay, CentraleSupélec, Laboratoire Génie Industriel, Gif-sur-Yvette, France; Ariel Cohen, MSc, IT Department, Innovation and Data, Assistance Publique Hôpitaux de Paris, Paris, France; Akram Redjdal, PhD, Sorbonne Université, Inserm,...

Publisher

American Society of Clinical Oncology (ASCO)

Link

https://ascopubs.org/doi/pdfdirect/10.1200/CCI.24.00026

Reference15 articles.

1. Natural language processing for automated quantification of bone metastases reported in free-text bone scintigraphy reports

2. Transformer versus traditional natural language processing: how much data is enough for automated radiology report classification?

3. The Carbon Footprint of Bioinformatics

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1. Response to Kempf et al on Methodological and Practical Aspects of a Distant Metastasis Detection Model;JCO Clinical Cancer Informatics;2024-08