Machine Learning in Cardiology: A Potential Real-World Solution in Low- and Middle-Income Countries

Global Access to Comprehensive Care for Paediatric and Congenital Heart Disease

Paediatric and congenital heart disease (PCHD) is common but remains forgotten on the global health agenda. Congenital heart disease is the most frequent major congenital anomaly, affecting approximately 1 in every 100 live births. In high-income countries, most children now live into adulthood, whereas in low- and middle-income countries, over 90% of patients do not get the care they need. Rheumatic heart disease is the most common acquired cardiovascular disease in children and adolescents. While almost completely eradicated in high-income countries, over 30-40 million people live with rheumatic heart disease in low- and middle-income countries. Challenges exist in the care for PCHD and, increasingly, adult congenital heart disease (ACHD) worldwide. In this review, we summarize the current status of PCHD and ACHD care through the health systems lens of workforce, infrastructure, financing, service delivery, information management and technology, and governance. We further highlight gaps in knowledge and opportunities moving forward to improve access to care for all those living with PCHD or ACHD worldwide.

The Utility of Language Models in Cardiology: A Narrative Review of the Benefits and Concerns of ChatGPT-4

Artificial intelligence (AI) and language models such as ChatGPT-4 (Generative Pretrained Transformer) have made tremendous advances recently and are rapidly transforming the landscape of medicine. Cardiology is among many of the specialties that utilize AI with the intention of improving patient care. Generative AI, with the use of its advanced machine learning algorithms, has the potential to diagnose heart disease and recommend management options suitable for the patient. This may lead to improved patient outcomes not only by recommending the best treatment plan but also by increasing physician efficiency. Language models could assist physicians with administrative tasks, allowing them to spend more time on patient care. However, there are several concerns with the use of AI and language models in the field of medicine. These technologies may not be the most up-to-date with the latest research and could provide outdated information, which may lead to an adverse event. Secondly, AI tools can be expensive, leading to increased healthcare costs and reduced accessibility to the general population. There is also concern about the loss of the human touch and empathy as AI becomes more mainstream. Healthcare professionals would need to be adequately trained to utilize these tools. While AI and language models have many beneficial traits, all healthcare providers need to be involved and aware of generative AI so as to assure its optimal use and mitigate any potential risks and challenges associated with its implementation. In this review, we discuss the various uses of language models in the field of cardiology.