Radiomics and Deep Learning as Important Techniques of Artificial Intelligence — Diagnosing Perspectives in Cytokeratin 19 Positive Hepatocellular Carcinoma
Fei Wang,1 Chunyue Yan,2 Xinlan Huang,3 Jiqiang He,1 Ming Yang,1 Deqiang Xian4 1Department of Radiology, Luzhou People’s Hospital, Luzhou, 646000, People’s Republic of China; 2Department of Emergency Medicine, Luzhou People’s Hospital, Luzhou, 646000, People’s Republic of China; 3Department of Medic...
Saved in:
Main Authors: | Wang F, Yan C, Huang X, He J, Yang M, Xian D |
---|---|
Format: | Article |
Language: | English |
Published: |
Dove Medical Press
2025-06-01
|
Series: | Journal of Hepatocellular Carcinoma |
Subjects: | |
Online Access: | https://www.dovepress.com/radiomics-and-deep-learning-as-important-techniques-of-artificial-inte-peer-reviewed-fulltext-article-JHC |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Intratumoral and Peritumoral Radiomics Based on DCE-MRI for Prediction of Microvascular Invasion Grading in Solitary Hepatocellular Carcinoma (≤3 cm)
by: Li Y, et al.
Published: (2025-05-01) -
A CT-Based Deep Learning Radiomics Scoring System for Predicting the Prognosis to Repeat TACE in Patients with Hepatocellular Carcinoma: A Multicenter Cohort Study
by: Dai Y, et al.
Published: (2025-07-01) -
Development and Validation of a Radiomics Nomogram Based on Magnetic Resonance Imaging and Clinicoradiological Factors to Predict HCC TACE Refractoriness
by: Dong Y, et al.
Published: (2025-07-01) -
Can Peritumoral Radiomics Based on MRI Predict the Microvascular Invasion Status of Combined Hepatocellular Carcinoma and Cholangiocarcinoma Before Surgery?
by: Guo L, et al.
Published: (2025-07-01) -
Non-structural role of cytokeratins in malignant neoplasms
by: M. A. Boldyshevskaya, et al.
Published: (2023-12-01)