Explainable Artificial Intelligence For The Detection and Characterisation of Stage B Heart Failure
arXiv:2606.30665v1 Announce Type: cross Abstract: Stage B heart failure is characterized by asymptomatic structural or functional cardiac abnormalities. Identifying individuals at this stage is clinically important, as early detection may enable targeted interventions to prevent progression to symptomatic disease. Explainable artificial intelligence (XAI) may support early detection, transparent risk stratification, and selection of clinically actionable interventions. This review examines the use of XAI in detecting and characterizing stage B heart failure. A literature search of Web of Scien
The proliferation of AI research, combined with increasing computational power and data availability in healthcare, is driving the application of advanced AI techniques like XAI to complex medical challenges.
Sophisticated readers should care because explainable AI in healthcare promises to accelerate diagnosis and treatment, while also addressing regulatory and ethical concerns around 'black box' AI models.
The ability to accurately and transparently detect early-stage diseases like heart failure will transform preventive medicine and personalized treatment pathways, improving patient outcomes and potentially reducing long-term healthcare costs.
- · AI healthcare tech companies
- · Cardiovascular diagnostics developers
- · Preventive medicine providers
- · Patients at risk of heart failure
- · Traditional diagnostic device manufacturers (if they don't adapt)
- · Hospitals with outdated IT infrastructure
- · Organizations slow to adopt AI
Early detection capabilities lead to earlier interventions and improved patient health outcomes for heart failure.
Increased trust in AI due to explainability drives wider adoption in other critical medical fields, accelerating the shift towards AI-powered healthcare.
Reduced healthcare burden from chronic diseases could free up resources for other medical research and public health initiatives globally.
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