Cardiovascular disease is still one of the top causes of death around the world, and AI is starting to play a bigger role in diagnosing, predicting, and treating it. A recent series of papers in The Lancet Digital Health explores how AI is changing heart care and the challenges that come with it. AI has the potential to do amazing things, like spotting risk factors early, analyzing heart scans, predicting outcomes, and even recommending treatments—helping doctors make better decisions faster.
But there’s a big issue: bias in AI. The data used to train AI systems often underrepresents people from poorer communities, rural areas, and ethnic minorities. This lack of representation means that the AI tools doctors rely on might not work as well for these groups. The result? Misdiagnoses or incorrect treatment recommendations, which could worsen the health gaps that already exist. In heart care, where missing a diagnosis can be life-threatening, the stakes are especially high.
These papers emphasize that while AI could revolutionize heart care, we need to tackle the issue of bias head-on. Solutions like using more diverse datasets and closely monitoring how AI tools are developed and used are critical. If we can get it right, AI has the power to not only improve care but also make it more equitable—especially for the people who need it most.