Predicting High-Grade Patterns in Stage I Solid Lung Adenocarcinoma: A Study of 371 Patients Using Refined Radiomics and Deep Learning-Guided CatBoost Classifier
Introduction This study aimed to devise a diagnostic algorithm, termed the Refined Radiomics and Deep Learning Features-Guided CatBoost Classifier (RRDLC-Classifier), and evaluate its efficacy in predicting pathological high-grade patterns in patients diagnosed with clinical stage I solid lung adeno...
Saved in:
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
SAGE Publishing
2024-12-01
|
| Series: | Technology in Cancer Research & Treatment |
| Online Access: | https://doi.org/10.1177/15330338241308610 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|