AIMC Topic: Triple Negative Breast Neoplasms
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Cohesive data analysis for the identification of prognostic hub genes and significant pathways associated with HER2 + and TN breast cancer types.
Scientific reports
Jul 2, 2025
Breast cancer is the most prevalent and lethal form of cancer being the utmost common medical concern of women. Breast cancer etiology implicates numerous cellular protein receptors such as estrogen receptors (ER), progesterone receptors (PR), and hu...
Prioritizing perturbation-responsive gene patterns using interpretable deep learning.
Nature communications
Jul 2, 2025
Spatially resolved transcriptomics enables mapping of multiplexed gene expression within tissue contexts. While existing methods prioritize spatially variable genes within a single slice, few address identifying genes with differential spatial expres...
A genotype-to-drug diffusion model for generation of tailored anti-cancer small molecules.
Nature communications
Jul 1, 2025
Despite advances in precision oncology, developing effective cancer therapeutics remains a significant challenge due to tumor heterogeneity and the limited availability of well-defined drug targets. Recent progress in generative artificial intelligen...
Prediction of axillary lymph node metastasis in triple negative breast cancer using MRI radiomics and clinical features.
Scientific reports
Jul 1, 2025
To develop and validate a machine learning-based prediction model to predict axillary lymph node (ALN) metastasis in triple negative breast cancer (TNBC) patients using magnetic resonance imaging (MRI) and clinical characteristics. This retrospective...
Image normalization techniques and their effect on the robustness and predictive power of breast MRI radiomics.
European journal of radiology
Mar 30, 2025
BACKGROUND AND PURPOSE: Radiomics analysis has emerged as a promising approach to aid in cancer diagnosis and treatment. However, radiomics research currently lacks standardization, and radiomics features can be highly dependent on acquisition and pr...
Harnessing Artificial Intelligence for Precision Diagnosis and Treatment of Triple Negative Breast Cancer.
Clinical breast cancer
Mar 8, 2025
Triple-Negative Breast Cancer (TNBC) is a highly aggressive subtype of breast cancer (BC) characterized by the absence of estrogen, progesterone, and HER2 receptors, resulting in limited therapeutic options. This article critically examines the role ...
Integrating ultrasound radiomics and clinicopathological features for machine learning-based survival prediction in patients with nonmetastatic triple-negative breast cancer.
BMC cancer
Feb 18, 2025
OBJECTIVE: This study aimed to evaluate the predictive value of implementing machine learning models based on ultrasound radiomics and clinicopathological features in the survival analysis of triple-negative breast cancer (TNBC) patients.
Glycosylation profiling of triple-negative breast cancer: clinical and immune correlations and identification of LMAN1L as a biomarker and therapeutic target.
Frontiers in immunology
Jan 10, 2025
INTRODUCTION: Breast cancer (BC) is the most prevalent malignant tumor in women, with triple-negative breast cancer (TNBC) showing the poorest prognosis among all subtypes. Glycosylation is increasingly recognized as a critical biomarker in the tumor...
Establishment and clinical application of a prognostic index for inflammatory status in triple-negative breast cancer patients undergoing neoadjuvant therapy using machine learning.
BMC cancer
Dec 20, 2024
OBJECTIVE: This study aims to establish a new prognostic index using machine learning models to predict the clinical outcomes of triple-negative breast cancer (TNBC) patients receiving neoadjuvant therapy.
The Value of Whole-Volume Radiomics Machine Learning Model Based on Multiparametric MRI in Predicting Triple-Negative Breast Cancer.
Journal of computer assisted tomography
Nov 25, 2024
OBJECTIVE: This study aimed to investigate the value of radiomics analysis in the precise diagnosis of triple-negative breast cancer (TNBC) based on breast dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and apparent diffusion coeffici...
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