[HTML][HTML] Application of radiomics-based multiomics combinations in the tumor microenvironment and cancer prognosis

W Kang, X Qiu, Y Luo, J Luo, Y Liu, J Xi, X Li… - Journal of Translational …, 2023 - Springer
The advent of immunotherapy, a groundbreaking advancement in cancer treatment, has
given rise to the prominence of the tumor microenvironment (TME) as a critical area of …

[HTML][HTML] Mammography with deep learning for breast cancer detection

L Wang - Frontiers in Oncology, 2024 - frontiersin.org
X-ray mammography is currently considered the golden standard method for breast cancer
screening, however, it has limitations in terms of sensitivity and specificity. With the rapid …

[HTML][HTML] Multi-view radiomics feature fusion reveals distinct immuno-oncological characteristics and clinical prognoses in hepatocellular Carcinoma

Y Gu, H Huang, Q Tong, M Cao, W Ming, R Zhang… - Cancers, 2023 - mdpi.com
Simple Summary Hepatocellular carcinoma is a widespread cancer with complex molecular
heterogeneity. Compared with invasive tissue sampling, the radiomics framework shows …

[HTML][HTML] Whole-tumor ADC texture analysis is able to predict breast cancer receptor status

M Szep, R Pintican, B Boca, A Perja, M Duma, D Feier… - Diagnostics, 2023 - mdpi.com
There are different breast cancer molecular subtypes with differences in incidence, treatment
response and outcome. They are roughly divided into estrogen and progesterone receptor …

[HTML][HTML] Breast Cancer Surrogate Subtype Classification Using Pretreatment Multi-Phase Dynamic Contrast-Enhanced Magnetic Resonance Imaging Radiomics: A …

L Kovačević, A Štajduhar, K Stemberger… - Journal of Personalized …, 2023 - mdpi.com
This study aimed to explore the potential of multi-phase dynamic contrast-enhanced
magnetic resonance imaging (DCE-MRI) radiomics for classifying breast cancer surrogate …

Development and validation of machine learning models for predicting HER2-zero and HER2-low breast cancers

X Huang, L Wu, Y Liu, Z Xu, C Liu… - British Journal of …, 2024 - academic.oup.com
Objectives To develop and validate machine learning models for human epidermal growth
factor receptor 2 (HER2)-zero and HER2-low using MRI features pre–neoadjuvant therapy …

多模态MRI 影像组学模型术前预测乳腺癌人表皮生长因子受体2 表达状态.

张韫, 黄昊, 尹亮, 王芷旋, 陆思远… - Chinese Journal of …, 2024 - search.ebscohost.com
目的探讨多模态MRI 影像组学模型术前预测乳腺癌人表皮生长因子受体2 (HER-2)
表达状态的价值. 方法纳入2021 年1 月至2023 年5 月镇江市第一人民医院经术后病理诊断的 …

[PDF][PDF] An Improved Fully Automated Breast Cancer Detection and Classification System.

T Shawly, AA Alsheikhy - Computers, Materials & Continua, 2023 - researchgate.net
More than 500,000 patients are diagnosed with breast cancer annually. Authorities
worldwide reported a death rate of 11.6% in 2018. Breast tumors are considered a fatal …

[HTML][HTML] Radiomic Prediction of CCND1 Expression Levels and Prognosis in Low-grade Glioma Based on Magnetic Resonance Imaging

K Zhao, H Zhang, J Lin, S Xu, J Liu, X Qian, Y Gu… - Academic …, 2024 - Elsevier
Ojectives Low-grade glioma (LGG) is associated with increased mortality owing to
recrudescence and the tendency for malignant transformation. Therefore, it is imperative to …

Magnetic resonance imaging-based machine learning radiomics predicts CCND1 expression level and survival in low-grade gliomas

K Zhao, H Zhang, J Lin, J Liu, S Xu, Y Gu, G Ren, X Lu… - 2023 - researchsquare.com
Low-grade glioma (LGG) is associated with increased mortality owing to the recrudescence
and tendency for malignant transformation. Therefore, novel prognostic biomarkers must be …