A comprehensive review of applications of artificial intelligence in echocardiography

Non-invasive imaging in acute decompensated heart failure with preserved ejection fraction

Non-invasive imaging plays an increasingly important role in emergency medicine, given the trend towards smaller, portable ultrasound devices, the integration of ultrasound imaging across diverse medical disciplines, and the growing evidence supporting its clinical benefits for the patient. Heart failure with preserved ejection fraction (HFpEF) provides a compelling illustration of the impactful role that imaging plays in distinguishing diverse clinical presentations of heart failure with numerous associated comorbidities, including pulmonary, renal, or hepatic diseases. While a preserved left ventricular ejection fraction might misguide the clinician away from diagnosing cardiac disease, there are several clues provided by cardiac, vascular, and lung ultrasonography, as well as other imaging modalities, to rapidly identify (decompensated) HFpEF. Congestion remains the primary reason why patients with heart failure (irrespective of ejection fraction) seek emergency care. Furthermore, comprehensive phenotyping is becoming increasingly important, considering the development of targeted treatments for conditions exhibiting HFpEF physiology, such as cardiac amyloidosis. Timely recognition in such cases has lasting implications for long-term outcomes.

Transformative Potential of AI in Healthcare: Definitions, Applications, and Navigating the Ethical Landscape and Public Perspectives

Artificial intelligence (AI) has emerged as a crucial tool in healthcare with the primary aim of improving patient outcomes and optimizing healthcare delivery. By harnessing machine learning algorithms, natural language processing, and computer vision, AI enables the analysis of complex medical data. The integration of AI into healthcare systems aims to support clinicians, personalize patient care, and enhance population health, all while addressing the challenges posed by rising costs and limited resources. As a subdivision of computer science, AI focuses on the development of advanced algorithms capable of performing complex tasks that were once reliant on human intelligence. The ultimate goal is to achieve human-level performance with improved efficiency and accuracy in problem-solving and task execution, thereby reducing the need for human intervention. Various industries, including engineering, media/entertainment, finance, and education, have already reaped significant benefits by incorporating AI systems into their operations. Notably, the healthcare sector has witnessed rapid growth in the utilization of AI technology. Nevertheless, there remains untapped potential for AI to truly revolutionize the industry. It is important to note that despite concerns about job displacement, AI in healthcare should not be viewed as a threat to human workers. Instead, AI systems are designed to augment and support healthcare professionals, freeing up their time to focus on more complex and critical tasks. By automating routine and repetitive tasks, AI can alleviate the burden on healthcare professionals, allowing them to dedicate more attention to patient care and meaningful interactions. However, legal and ethical challenges must be addressed when embracing AI technology in medicine, alongside comprehensive public education to ensure widespread acceptance.