Arts en algoritme

Artificial intelligence (AI) is transforming healthcare through its ability to analyse vast amounts of data and recognize subtle patterns. This article explores three key areas where AI shows promise: administrative processes, diagnostic support, and patient monitoring. While AI systems can enhance medical diagnostics it also introduces new challenges. Modern AI models, unlike earlier rule-based systems, use millions of parameters that reduce explainability and complicate already existing accountability questions. Additionally, biases in training data can perpetuate healthcare inequalities. Successful implementation requires hybrid systems where healthcare professionals and AI collaborate effectively, supported by appropriate interfaces and digital literacy. Despite its potential, hardware requirements and integration with legacy systems often slow adoption in clinical settings. The future of healthcare lies not in AI alone, but in the intelligent combination of human expertise and machine capabilities.

Conflict of interest and financial support: none declared.