Abstract
Computer-interpretable guidelines (CIGs) exploit the scientific strength of evidence-based medicine to make recommendations available in clinical decision support systems. However, systems that deploy them have not been widely successful, in part due to the limitations of CIG frameworks in the adoption of inclusive and open technologies and the use of artificial intelligence techniques as tools to make their systems stronger and more adaptable. In this work, we propose a web-based CIG framework to tackle some of these challenges and facilitate the integration of CIG-based advice not only in the everyday activities of health care professionals, but also in the lives of whoever may need it.
Published Version
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