Radiology AI for Diagnosis and Imaging eXcellence (RADIX)
Project Overview
The Radix project aims to develop and validate a series of artificial intelligence (AI) models for analyzing medical imaging data with the overall objective of improving the accuracy and efficiency of medical diagnoses, thereby reducing the burden of disease and improving patient outcomes.
Radix objectives
- To develop and train six distinct AI models for analyzing medical imaging data, including X-rays, CT scans, MRI scans, ultrasound, fluoroscopy, nuclear medicine scans, and PET/CT scans.
- To validate the performance of these models using large-scale, diverse datasets from multiple healthcare settings.
- To compare the diagnostic accuracy and efficiency of the AI models with standard radiological interpretations by human experts.
- To investigate the impact of AI-assisted radiology on patient outcomes, such as diagnostic accuracy, treatment decisions, and long-term prognosis.
Advancing Healthcare
with AI
Medical imaging’s potential is vast, but interpreting complex images accurately is challenging. The Radix Project combines medical expertise with AI proficiency to develop and validate AI models for various imaging modalities. Our goal is to enhance diagnostic accuracy, enable early disease detection, and empower healthcare providers with transformative tools.
Partnering with Tanzanian hospitals, the Radix Project employs mixed methods, including surveys, interviews, observations, and medical record reviews. We focus on improving diagnostic efficiency, reducing healthcare costs, and broadening access to quality healthcare.
