Meeting
2023 ASCO Breakthrough
Automated classification of disease response in radiology reports using natural language processing.
Authors
Hai Xiang Ong
Nanyang Technological University, Singapore, Singapore
Hai Xiang Ong , Yiyu Cai , Zi Meng Yi , Wen Hui Tee , Ryan Shea Tan Ying Cong , Wei Chong Tan , Abu Bakr Azam
Disclaimer
This material on this page is ©2024 American Society of Clinical Oncology, all rights reserved. Licensing available upon request. For more information, please contact licensing@asco.org
Poster Details
Session Type
Poster Session
Session Title
Poster Session B
Track
Gastrointestinal Cancer,Gynecologic Cancer,Head and Neck Cancer,Quality of Care,Genetics/Genomics/Multiomics,Healthcare Equity and Access to Care,Healthtech Innovations,Models of Care and Care Delivery,Population Health,Viral-Mediated Malignancies
Sub Track
Artificial Intelligence/Deep Learning
Citation
JCO Global Oncology 9, 2023 (suppl 1; abstr 108)
DOI
10.1200/GO.2023.9.Supplement_1.108
Abstract #
108
Poster Bd #
G3
Abstract Disclosures
Similar Posters
Poster
2024 ASCO Annual Meeting
From criteria to clinic: How updated SLiM CRAB criteria influence multiple myeloma diagnostic activity.
First Author: Mengmeng Ji
Poster
2016 ASCO Annual Meeting
Natural language processing (NLP) software use in the discovery of incidental lung cancers.
First Author: Melissa Lynne Johnson
Poster
2024 ASCO Annual Meeting
AI-based approach to enable proactive identification of early lung cancer: A retrospective population health study and economic model.
First Author: William Ricketts
Poster
2024 ASCO Genitourinary Cancers Symposium
The Capio Prostate Cancer Center model for prostate cancer diagnostics using Stockholm3, MRI, and targeted biopsies: Real-world evidence from 2018 to 2022.
First Author: Thorgerdur Palsdottir