Research graph
References from Habitat imaging based on DCE-MRI for differentiating luminal and non-luminal subtypes of breast cancer: a two-center study. Local targets link to admitted publications; unresolved targets remain external evidence.
Global patterns and trends in breast cancer incidence and mortality across 185 countries
10.1038/s41591-025-03502-3 · 2025 · External reference
Breast cancer treatment: a review
10.1001/jama.2018.19323 · 2019 · External reference
The role of progesterone receptors in breast cancer
10.2147/dddt.s336643 · 2022 · External reference
Breast cancer-epidemiology, risk factors, classification, prognostic markers, and current treatment strategies-an updated review
10.3390/cancers13174287 · 2021 · External reference
Concordance of the molecular subtype classification between core needle biopsy and surgical specimen in primary breast cancer
10.1007/s00404-021-05996-x · 2021 · External reference
Deep learning-enabled breast cancer hormonal receptor status determination from base-level H&E stains
10.1038/s41467-020-19334-3 · 2020 · External reference
Radiomics in breast cancer classification and prediction
10.1016/j.semcancer.2020.04.002 · 2021 · External reference
MRI-based habitat imaging in cancer treatment: current technology, applications, and challenges
10.1186/s40644-024-00758-9 · 2024 · External reference
Contrast-enhanced CT-based habitat radiomics for distinguishing low-risk thymomas from high-risk thymomas: a multicenter study
10.1007/s11604-025-01854-x · 2026 · External reference
Clinical-radiomics nomogram based on the fat-suppressed T2 sequence for differentiating luminal and non-luminal breast cancer
10.3389/fonc.2024.1451414 · 2024 · External reference
The value of multiparametric MRI-based combined intratumoral and peritumoral radiomics in differentiating luminal and non-luminal molecular subtypes of breast cancer: a multicenter study
10.21037/gs-2025-83 · 2025 · External reference
Development and validation of an ultrasound-based radiomics nomogram for predicting the luminal from non-luminal type in patients with breast carcinoma
10.3389/fonc.2022.993466 · 2022 · External reference
SLIC superpixels compared to state-of-the-art superpixel methods
10.1109/tpami.2012.120 · 2012 · External reference
Habitat radiomics based on MRI for predicting metachronous liver metastasis in locally advanced rectal cancer: a two-center study
10.1016/j.acra.2025.02.046 · 2025 · External reference
Modulation format identification using the Calinski-Harabasz index
10.1364/ao.448043 · 2022 · External reference
Deep learning in multi-modal breast cancer data fusion: a literature review
10.21037/qims-2024-2903 · 2025 · External reference
Longitudinal DCE MRI vascular textures: radiologic and biologic insights for pCR prediction in HER2-negative breast cancer
10.1148/ryai.250734 · 2026 · External reference
Multimodal prediction model integrating clinical parameters, peritumoral and habitat-based radiomics for preoperative differentiation of follicular thyroid carcinoma from adenoma: a two-center study
10.1016/j.acra.2025.11.013 · 2026 · External reference
Preoperative prediction of axillary lymph node metastasis in breast cancer based on intratumoral and peritumoral DCE-MRI radiomics nomogram
10.1155/2022/6729473 · 2022 · External reference
3T MRI-radiomic approach to predict for lymph node status in breast cancer patients
10.3390/cancers13092228 · 2021 · External reference
Application of DCE-MRI radiomics and heterogeneity analysis in predicting luminal and non-luminal subtypes of breast cancer
10.3389/fonc.2025.1523507 · 2025 · External reference
Application of DCE-MRI radiomics signature analysis in differentiating molecular subtypes of luminal and non-luminal breast cancer
10.3389/fmed.2023.1140514 · 2023 · External reference
DCE-MRI radiomics analysis in differentiating luminal A and luminal B breast cancer molecular subtypes
10.1016/j.acra.2022.04.004 · 2023 · External reference
Tumor habitat-derived radiomics features in pretreatment CT scans for predicting concurrent chemoradiotherapy responses in nasopharyngeal carcinoma: a retrospective study
10.21037/qims-24-1642 · 2025 · External reference
Habitat imaging with tumoral and peritumoral radiomics for prediction of lung adenocarcinoma invasiveness on preoperative chest CT: a multicenter study
10.2214/ajr.24.31675 · 2024 · External reference
Habitat radiomics based on MRI for predicting platinum resistance in patients with high-grade serous ovarian carcinoma: a multicenter study
10.1016/j.acra.2023.11.038 · 2024 · External reference
Quantification of intratumoral heterogeneity using habitat-based MRI radiomics to identify HER2-positive, -low and -zero breast cancers: a multicenter study
10.1186/s13058-024-01921-7 · 2024 · External reference
Prediction of high-risk capsule characteristics for recurrence of pleomorphic adenoma in the parotid gland based on habitat imaging and peritumoral radiomics: a two-center study
10.1016/j.acra.2025.01.030 · 2025 · External reference
Evaluating fusion models for predicting occult lymph node metastasis in tongue squamous cell carcinoma
10.1007/s00330-025-11473-9 · 2025 · External reference
MRI-based habitat radiomics combined with vision transformer for identifying vulnerable intracranial atherosclerotic plaques and predicting stroke events: a multicenter, retrospective study
10.1016/j.eclinm.2025.103186 · 2025 · External reference
Constructing the optimal classification model for benign and malignant breast tumors based on multifeature analysis from multimodal images
10.1007/s10278-024-01036-7 · 2024 · External reference
Machine learning-based identification of kbhb-affected tumor cell subsets as prognostic and therapeutic targets in breast cancer
10.1186/s12967-025-07555-3 · 2025 · External reference
Integrating deep learning features from mammography with SHAP values for a machine learning model predicting over 5-year recurrence of breast ductal carcinoma in situ post-lumpectomy
10.3389/fimmu.2025.1681072 · 2025 · External reference
Fast, accurate, and racially unbiased pan-cancer tumor-only variant calling with tabular machine learning
10.1038/s41698-022-00340-1 · 2023 · External reference
Multiparametric MRI-based interpretable machine learning radiomics model for distinguishing between luminal and non-luminal tumors in breast cancer: a multicenter study
10.1016/j.acra.2025.03.010 · 2025 · External reference
An interpretable machine learning model based on computed tomography radiomics for predicting programmed death ligand 1 expression status in gastric cancer
10.1186/s40644-025-00855-3 · 2025 · External reference
