Integrating AI to analyze imaging data allows early recognition of heart disease

Integrating artificial intelligence (AI) to analyze imaging data allows early recognition of heart disease, saving patients' time, money and, most importantly, lives. Find out how at ICNC 2019, the International Conference on Nuclear Cardiology and Cardiac CT (ICNC) - co-organised by the American Society of Nuclear Cardiology (ASNC), the European Association of Cardiovascular Imaging (EACVI) of the European Society of Cardiology (ESC), and the European Association of Nuclear Medicine (EANM).

The international meeting will be held 12 to 14 May at the Lisbon Congress Centre (CCL) in Portugal.

Explore the scientific programme and discover how scientists and clinicians are pushing the boundaries of knowledge to improve prevention, diagnosis, and treatment of heart disease.

The meeting will showcase 300 novel studies, including:

• Use of AI to select patients for treatment.
• And on the flipside - how AI prevents unneeded tests.
• Deep learning to predict cardiovascular events.
• Artificial neural networks, a type of AI, teach beginners to interpret complex imaging results.
• Which patients are most at risk of death? Machine learning has the answer.
• Cardiac imaging to predict cardiovascular outcome after liver transplantation.
• New insights on valve disease from a remote population with a subsistence-based, physically active lifestyle.
• Duration of cocaine use and risk of heart disease.
• Additional costs of cardiac imaging in obese patients.
• New protocol to improve cardiac image quality in heavier patients.

ICNC is the meeting where more than 600 clinicians and scientists from around the world gather for the latest updates on state-of-the-art nuclear cardiology and cardiac computed tomography (CT). Over 2.5 days and 30-plus scientific sessions, more than 120 global experts will present advances in this rapidly moving field.

Dr Danilo Neglia, EACVI scientific programme co-chairperson, said: "The congress focuses on emerging topics in cardiovascular diseases, including how to integrate advanced imaging modalities for early recognition of disease and personalised patient management. We will see how the fast development of non-invasive nuclear and CT imaging technology can help us avoid invasive or unnecessary procedures, better define the risk of the single patient, and guide treatment in the most cost-effective way."

Dr Wael Jaber, ASNC scientific programme co-chairperson, said: "This conference will bring together cardiac imaging experts to look at the horizon going forward in non-invasive imaging of cardiovascular diseases. Sessions will be interactive and feature live reporting from the Cleveland Clinic of image interpretation in patients undergoing single photon emission computed tomography (SPECT) and positron emission tomography (PET)."1

Dr Fabien Hyafil, EANM scientific programme co-chairperson, said: "We are at a new frontier where artificial intelligence can integrate clinical and imaging data to provide a 'decision support system' to the clinician for effective diagnosis and treatment. Original scientific research will be presented in this and other areas of innovation."