Robotics & Machine Learning Daily News2024,Issue(Mar.4) :56-57.

Huazhong University of Science and Technology Reports Findings in Artificial Intelligence (Advances in the Application of Artificial Intelligence in Fetal Echocardiography)

Robotics & Machine Learning Daily News2024,Issue(Mar.4) :56-57.

Huazhong University of Science and Technology Reports Findings in Artificial Intelligence (Advances in the Application of Artificial Intelligence in Fetal Echocardiography)

扫码查看

Abstract

New research on Artificial Intelligence is the subject of a report. According to news reporting out of Wuhan, People’s Republic of China, by NewsRx editors, research stated, “Congenital heart disease is a severe health risk for newborns. Early detection of abnormalities in fetal cardiac structure and function during pregnancy can help patients seek timely diagnostic and therapeutic advice, and early intervention planning can significantly improve fetal survival rates.” Our news journalists obtained a quote from the research from the Huazhong University of Science and Technology, “Echocardiography is one of the most accessible and widely used diagnostic tools in the diagnosis of fetal congenital heart disease. However, traditional fetal echocardiography has limitations due to fetal, maternal, and ultrasound equipment factors and is highly dependent on the skill level of the operator. Artificial intelligence (AI) technology, with its rapid development utilizing advanced computer algorithms, has great potential to empower sonographers in time-saving and accurate diagnosis and to bridge the skill gap in different regions. In recent years, AI-assisted fetal echocardiography has been successfully applied to a wide range of ultrasound diagnoses.”

Key words

Wuhan/People’s Republic of China/Asia/Artificial Intelligence/Cardiology/Cardiovascular/Diagnosis/Diagnostic Techniques and Procedures/Diagnostics and Screening/Doppler Echocardiography/Echocardiography/Emerging Technologies/Health and Medicine/Machine Learning/Risk and Prevention

引用本文复制引用

出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

ISSN:
段落导航相关论文