Meeting
2023 ASCO Annual Meeting
Assessment of electronic health record (EHR) –based machine learning (ML) in predicting risk of brain metastasis among patients with early-stage non–small-cell lung cancer (eNSCLC).
Authors
Hossein Honarvar
ConcertAI, Cambridge, MA
Hossein Honarvar , Deep K Hathi , Ravi Bharat Parikh , Rahul K Das
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
Central Nervous System Tumors
Track
Central Nervous System Tumors
Sub Track
Brain Metastases
Citation
J Clin Oncol 41, 2023 (suppl 16; abstr 2036)
DOI
10.1200/JCO.2023.41.16_suppl.2036
Abstract #
2036
Poster Bd #
393
Abstract Disclosures
Similar Posters
Poster
2023 ASCO Annual Meeting
Development of a novel blood-based RNA gene expression platform for early-stage lung cancer diagnosis.
First Author: Martin J Keiser III
Poster
2023 ASCO Annual Meeting
Development and validation of a prediction model for the recurrence of stage 1 EGFR mutation positive NSCLC in patients using machine learning with WES-based gene sets.
First Author: Akiko Tateishi
Poster
2023 ASCO Annual Meeting
The RESECT study: Factors associated with overall survival (OS) and relapse-free survival (RFS) among patients with stages I–III resected NSCLC without known EGFR mutations.
First Author: Jhanelle Elaine Gray
Poster
2023 ASCO Annual Meeting
A radiomic-based predictive model of lung adenocarcinoma brain metastases and molecular subtypes.
First Author: Xiancheng Wu