Stable MRI Radiomics Predicts Chemotherapy Response in Breast Cancer
A retrospective multicenter study of 686 patients with HR+/HER2− breast cancer established a stability-driven MRI radiomics model that accurately predicted ...
Tag: radiomics
CT Radiomics Detects Lung Scarring in Scleroderma Patients as Well as Clinical Data, Small Study Finds
An exploratory study of 67 systemic sclerosis patients found that machine learning models built from HRCT radiomic features detected interstitial ...
Radiomics Accurately Identifies Vulnerable Carotid Artery Plaques in Comprehensive Review
A systematic review of 28 studies reveals that radiomics models identify vulnerable carotid artery plaques more effectively than conventional stenosis ...
CT radiomics model predicts poor chemotherapy response in esophageal cancer before treatment
A dual-center study found that a CT-based radiomics model using four texture features predicted poor pathological response to neoadjuvant chemotherapy ...
AI biomarkers show promise for predicting cancer immunotherapy response, review finds
A new review finds AI-derived biomarkers show promising, though variable, performance in predicting cancer immunotherapy response across tumor types.
AI Cannot Yet Replace Lymph Node Surgery After Negative Prostate PET
A systematic scoping review finds that current AI evidence does not support omitting extended pelvic lymph-node dissection after a negative ...
MRI-based machine learning model predicts aggressive tumor budding in breast cancer before surgery
An interpretable MRI-based machine learning nomogram predicted tumor budding grade in breast cancer with AUCs of 0.906, 0.845 and 0.825 ...
CT Imaging Model Predicts Kidney Cancer Grade in Older Patients
A multicenter retrospective study published in Frontiers in Oncology reports that a multimodal artificial intelligence model can predict the histological ...
AI Model Combines CT Scans and Body Composition to Predict Gastric Cancer Chemotherapy Response
A multimodal machine learning model integrating clinical data, tumor radiomics, and body composition from CT scans predicted neoadjuvant chemotherapy response ...
MRI Habitat Analysis Identifies High-Risk Prostate Cancer
A two-center study developed a biparametric MRI habitat analysis framework that effectively identifies pathologically high-risk prostate cancer, showing superior discrimination ...
Ultrasound radiomics with machine learning shows modest accuracy in assessing fetal ventricular disproportion
A retrospective single-centre study found that echocardiography-based radiomics with machine learning achieved only moderate accuracy in distinguishing fetal ventricular disproportion ...
Artificial Intelligence Enhances Prostate Cancer Recurrence Prediction Using Magnetic Resonance Imaging
A critical narrative review synthesizes evidence from over eighty studies demonstrating that artificial intelligence applied to multiparametric magnetic resonance imaging ...
Nested CT Habitat Score Distinguishes Lung Adenocarcinoma Grades in Multi-Center Study
A retrospective two-center study of 650 patients found a CT-derived nested habitats score discriminated IASLC Grade 1 from Grade 2 ...
CT Histogram Radiomics Accurately Distinguishes Middle Ear Cholesteatoma
A retrospective study demonstrates that histogram-based radiomic texture analysis of temporal bone HRCT scans accurately differentiates middle ear cholesteatoma from ...
Machine Learning Model Integrates Multimodal Data to Stratify Glioblastoma Survival Risk
A multimodal machine learning nomogram combining clinical, radiomics, and pathomics features improved overall survival risk stratification in patients with IDH-wildtype ...
Artificial Intelligence Models Show Moderate Accuracy in Detecting Trigeminal Neuralgia Phenotypes
A systematic review and meta-analysis indicates that magnetic resonance imaging artificial intelligence models achieve moderate discriminative performance for identifying affected ...
MRI-Based Radiogenomic Model Predicts Survival in Glioblastoma via IL-19
A machine-learning radiogenomic model predicts IL19 expression from glioblastoma MRI scans and separates patients into survival groups.
MRI Radiomics and Vascular Gene Profiles Capture Different Sides of Breast Cancer Tumor Blood Vessels
A study of 932 breast cancer patients finds that DCE-MRI radiomic subgroups and vascular gene-expression subgroups capture complementary, non-overlapping dimensions ...
CT radiomics model predicts which ureteral stones will pass without surgery
A machine learning model combining CT radiomics with clinical variables predicted spontaneous ureteral stone passage within four weeks with an ...
CT Radiomics Model Predicts Outcomes After Bleeding Stroke Across Four Hospitals
A multicenter study combined CT-derived radiomic features with clinical data in an XGBoost model that predicted outcomes after aneurysmal subarachnoid ...
