abstract

Predicting Treatment Response to Neoadjuvant Chemotherapy in Osteosarcoma Patients using MRI-based Radiomics and Deep Learning
Predicting Treatment Response to Neoadjuvant Chemotherapy in Osteosarcoma Patients using MRI-based Radiomics and Deep Learning
Structured Clinical Data Extraction from Free-Text Reports with Large Language Models (LLMs): From Benchmarking to Knowledge Graphs
AI in Radiological Imaging of Soft-Tissue and Bone Tumours: A Systematic Review Evaluating Against CLAIM and FUTURE-AI Guidelines
Automated AI-Based Segmentation of Colorectal Liver Metastases: A Discovery Study on Histopathological Whole-Slide Images
Early health technology assessment for an artificial intelligence tool to detect incidental pulmonary embolisms on computed tomography
Evaluating IVIM and ADC Parameters to Differentiate Benign and Malignant Soft-Tissue Lesions
Multi-Center External Validation of an Automated Method Segmenting and Differentiating Atypical Lipomatous Tumors from Lipomas Using Radiomics and Deep-Learning on MRI
Predicting Failure of Active Surveillance in Desmoid-Type Fibromatosis Using Radiomics: An International Multi-Center Study
The liver artificial intelligence (LAI) consortium: a benchmark dataset and optimised machine learning methods for MRI-based diagnosis of solid-appearing liver lesions