Machine learning techniques such as combining machine learning with echocardiography and electrocardiography (ECG), show promising results in diagnosing pulmonary arterial hypertension (PAH), offering a potential noninvasive alternative to traditional invasive methods, according to a study published in Frontiers in Cardiovascular Medicine.
One significant advantage of ML approaches is their ability to integrate complex datasets noninvasively, reducing procedural risks while maintaining diagnostic precision. These advancements align with the growing trend of personalized medicine, ensuring patients receive tailored care based on precise, data-driven insights.
【MORE】