Automated AI-generated measurements combined with annotated CT images can improve treatment planning and help referring physicians and patients better understand their disease, explained Sarah Jane Rinehart, MD, director of cardiac imaging with Charleston Area Medical Center.
Raquel Roman, chair of the Radiology Business Management Association (RBMA) Young Professionals Committee, and director of growth at Essential Radiology, explains how the group mentors the next generation leaders.
Rads should learn more about employment negotiations before signing a contract, says Seetharam Chadalavada, MD, vice chair of radiology informatics at the University of Cincinnati.
As the population of patients with adult congenital heart disease grows, they are presenting to adult cardiology clinics and being imaged with CT. Many also do not have access or cannot be imaged by MRI, said Renee Bullock-Palmer, MD.
Validation and testing of all algorithms is needed to eliminate any biases in the data used to train the AI, according to Julius Bogdan, vice president and general manager of the HIMSS Digital Health Advisory Team for North America.
Joao Cavalcante, MD, director, cardiac MRI and structural CT labs, Minneapolis Heart Institute, discusses the use of cardiac CT imaging to plan and guide structural heart procedures.
Rebecca T. Hahn, MD, Director of Interventional Echocardiography at the Columbia Structural Heart and Valve Center, discusses some of the trends in the growing use of interventional echocardiographic guidance in transcatheter structural heart procedures.
Julius Bogdan, vice president and general manager of the Healthcare Information and Management Systems Society (HIMSS) Digital Health Advisory Team for North America, explains several key artificial intelligence (AI) trends he sees across healthcare.
Bibb Allen, MD, FACR, chief medical officer of the American College of Radiology (ACR) Data Science Institute, discusses multiple factors involved in the adoption rate of artificial intelligence in radiology.
Automated AI-generated measurements combined with annotated CT images can improve treatment planning and help referring physicians and patients better understand their disease, explained Sarah Jane Rinehart, MD, director of cardiac imaging with Charleston Area Medical Center.
Two advanced algorithms—one for CAC scores and another for segmenting cardiac chamber volumes—outperformed radiologists when assessing low-dose chest CT scans.
"Gen AI can help tackle repetitive tasks and provide insights into massive datasets, saving valuable time," Thomas Kurian, CEO of Google Cloud, said Tuesday.
