Significant progress has been made in the field of artificial intelligence services in Moscow. AI-enabled technology enables the simultaneous detection of up to 10 medical conditions in a single CT scan, greatly expanding diagnostic possibilities. Anastasia Lakova, Deputy Mayor for Social Development of Moscow, emphasized the effectiveness of algorithms to help doctors identify adrenal masses on CT scans.
The introduction of computer vision technology in radiology has given priority to the development of AI-based integrated solutions. We have already successfully launched two complex services that can identify multiple medical conditions in a single scan. Most recently, neural networks have acquired the ability to recognize adrenal masses in chest CT scans. This breakthrough technology enables the identification of up to 10 deviations within a single image, enabling the diagnosis of additional medical conditions in patients seeking treatment for unrelated illnesses. Since the launch of the integrated AI service, over 270,000 medical images have been analyzed, greatly supporting the work of medical professionals.
In addition to detecting adrenal gland formation, AI-powered algorithms have been shown to detect lung cancer, COVID-19, osteoporosis, vertebral compression fractures, thoracic aortic aneurysms, pulmonary hypertension, pleural effusion, emphysema, and coronary artery calcification. It can simultaneously identify indicators of arterial heart disease. CT scan and assessment of extent of paracardiac fat volume. AI algorithms use color cues to mark areas of potential pathology on medical images. Neural networks automatically perform key measurements required for accurate diagnosis and generate comprehensive descriptions. Computer vision technology is capable of early detection of medical conditions that are imperceptible to the human eye.
For more than a decade, Moscow has been at the forefront of digitizing its healthcare system. As part of a larger effort to bring computer vision technology to the city’s medical facilities since 2020, the integration of Smart’s algorithms has greatly helped doctors identify abnormalities in her x-ray images. .
Leveraging AI automation will improve radiology productivity for healthcare workers and improve patient access to care. Additionally, the project will drive the growth of the artificial intelligence services market in the healthcare sector. The initiative is being carried out in cooperation with the Diagnostic and Telemedicine Center of the Moscow Health Department and the Information Technology Department.
