Tag: radiomics

A Chinese proof-of-concept study found that a CT radiomics model predicting early response to radiotherapy in elderly esophageal cancer patients ...

A hybrid deep learning and radiomics framework can detect subjective cognitive decline, the earliest preclinical stage of Alzheimer's disease, from ...

A multi-task deep learning model that fuses pretreatment MRI and whole slide pathology images outperformed standard staging in predicting chemotherapy ...

A new study shows that an interpretable AI model fusing 18F-PSMA-1007 PET/CT and multiparametric MRI can predict prostate cancer aggressiveness ...

A multicenter study shows that a hybrid model combining MRI radiomics, delta features, and clinical variables predicts overall survival in ...

A two-center study trained a deep learning radiomics model on routine breast ultrasound images to predict sentinel lymph node metastasis ...

Researchers have developed a registration-consistent framework that turns routine daily cone-beam CT scans into a longitudinal measure of tumour texture ...

A comprehensive review finds that while artificial intelligence shows striking performance in detecting, staging, and predicting gastric cancer outcomes, most ...

A new systematic review of 28 studies finds that deep learning detects vulnerable carotid plaques with a pooled AUC of ...

A new meta-analysis of eleven studies finds that AI-driven analysis of routine contrast-enhanced CT scans can predict the Ki-67 proliferation ...

Chinese researchers have built a machine-learning nomogram that combines biparametric MRI radiomics, clinical variables, and PI-RADS scores to predict clinically ...

Researchers have built an interpretable 2.5D deep learning model that fuses contrast-enhanced CT features with clinical variables to reliably distinguish ...

A new deep learning framework called MedSegNet-AXU segments multiple sclerosis lesions from 3D MRI with a 98.58 percent Dice score ...

An exploratory study of 61 breast cancer patients found only weak, statistically fragile links between regional tumor immune-stromal composition and ...

A two-center study shows that an MRI-based radiomics nomogram using a multilayer perceptron classifier can distinguish malignant from benign orbital ...

Researchers in Guangzhou built a machine-learning model that combines MRI radiomics and clinical variables to predict lymphovascular invasion in gastric ...

A multicenter study shows a hybrid deep learning model combining CNN and graph convolutional networks can predict malignancy in BI-RADS ...

Researchers in Nanjing developed an interpretable machine learning model that analyzes MRI tumor subregions to predict prostate cancer aggressiveness noninvasively ...

A Chinese research team has built a radiomics and deep learning model that predicts brain invasion in meningiomas from routine ...

A two-center study shows that radiomic analysis of MR cytometry parameter maps outperforms mean-value-based diffusion MRI metrics for distinguishing benign ...