Precision lung cancer screening from CT scans using a VGG16-based convolutional neural network.

ABSTRACT:

Objective

The research aims to develop an advanced and precise lung cancer screening model based on Convolutional Neural Networks (CNN).

Methods

Based on the health medical big data platform of Shandong University, we developed a VGG16-Based CNN lung cancer screening model. This model was trained using the Computed Tomography scans data of patients from Pingyi Traditional Chinese Medicine Hospital in Shandong Province, from January to February 2023. Data augmentation techniques, including random resizing, cropping, horizontal flipping, color jitter, random rotation and normalization, were applied to improve model generalization. We used five-fold cross-validation to robustly assess performance. The model was fine-tuned with an SGD optimizer (learning rate 0.001, momentum 0.9

SUBMITTER: Xu H 

PROVIDER: S-EPMC11369893 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature