What are the benefits of accurately assessing plaque burden in your patients with suspected coronary artery disease (CAD)? Listen to two cardiologists discuss the advantages of using a coronary CTA pathway along with AI-based plaque analysis and physiology to understand a patient’s risks of cardiovascular events.
Data standardization in medical imaging has evolved from a technical necessity to a strategic imperative, requiring an ontology-level approach to patient studies for optimization. According to Radiologist Cheryl Petersilge and CIO Matt Dewey, hospitals and imaging groups are increasingly implementing advanced standardization solutions. The benefits are significant, including greater radiologist efficiency, improved access to imaging exams, and increased accuracy in both human and AI-driven interpretations.
Despite the use of effective drug and device therapies, many patients with HFrEF continue to experience worsening symptoms and disease progression. Barostim is a novel device therapy that works with drug therapies to target the neurohormonal pathways responsible for heart failure progression and symptoms. Patients feel better and their quality of life improves.
Lesion-specific physiology matters! Three leading experts review cases that demonstrate why and how lesion-specific physiology can inform treatment for patients with CAD and lessons learned from 10 years of FFRCT interpretation.
We need to change the conversation on women, chest pain and coronary artery disease (CAD). Two leading experts will review women’s unique biology, risk factors, and presenting symptoms of heart disease during this webinar. They also will discuss better ways to detect and diagnose CAD, and how cardiac CT and FFRCT can identify those at-risk and in need of treatment. Join us to learn how cardiovascular (CV) teams can identify women at risk of CAD who are most likely to benefit from further testing and treatment.
We asked the questions you want to: Why is imaging ripe for AI? How will improvements in image processing and reconstruction, quality control and work list prioritization improve the practice of radiology?
Learn how ML algorithms are helping radiologists to improve diagnosis, find more cancers, reduce biopsies and increase efficiency, and what IT departments need to know to deploy AI apps.