Weakly supervised large-scale pancreatic cancer detection using multi-instance learning.

ABSTRACT:

Introduction

Early detection of pancreatic cancer continues to be a challenge due to the difficulty in accurately identifying specific signs or symptoms that might correlate with the onset of pancreatic cancer. Unlike breast or colon or prostate cancer where screening tests are often useful in identifying cancerous development, there are no tests to diagnose pancreatic cancers. As a result, most pancreatic cancers are diagnosed at an advanced stage, where treatment options, whether systemic therapy, radiation, or surgical interventions, offer limited efficacy.

Methods

A two-stage weakly supervised deep learning-based model has been proposed to identify pancreatic tumors using computed tomography (CT) images from Henry Ford Health (HFH) and publicly available Memorial Sloan K

SUBMITTER: Mandal S 

PROVIDER: S-EPMC11390448 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature