Validation of an AI-powered IASLC grading system for lung adenocarcinoma
Principal Investigator
Name
Shuoyu Xu
Degrees
Ph.D.
Institution
Bio-totem Pte Ltd
Position Title
Chief Scientific Officer
Email
About this CDAS Project
Study
NLST
(Learn more about this study)
Project ID
NLST-1290
Initial CDAS Request Approval
Jul 8, 2024
Title
Validation of an AI-powered IASLC grading system for lung adenocarcinoma
Summary
The International Association for the Study of Lung Cancer (IASLC) Pathology Committee recently proposed a new histological grading system for invasive lung adenocarcinoma. However, manual grading is time-consuming and subject to inter-observer variability. This project aims to validate an artificial intelligence (AI) system to automate and standardize the IASLC grading process. This AI-powered IASLC grading system has the potential to standardize lung adenocarcinoma grading, improve prognostic accuracy, and enhance treatment planning.
Aims
Aim 1: Evaluate the concordance between AI-generated and pathologist-assigned IASLC grades using a subset of cases from the National Lung Screening Trial (NLST) dataset.
Aim 2: Assess the prognostic accuracy of AI-generated IASLC grades using the complete NLST dataset.
Collaborators
N/A