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CardioX is designed to support clinicians with responsible, interpretable AI. The system prioritises transparency, patient data protection, and safe clinical use through strong governance and ethical framing.
Decision Support, Not Diagnosis
CardioX provides risk insights to support clinical judgement. It does not replace clinical expertise or provide a final diagnosis. Responsibility for clinical decisions remains with qualified healthcare professionals.
Secure Patient Data Handling
Patient data is stored securely with encryption in transit and at rest, alongside strict access controls. This ensures confidentiality and supports safe handling of sensitive clinical information in healthcare environments.
Transparency & Model Evaluation
CardioX is evaluated using established performance metrics (e.g., ROC-AUC) to assess predictive quality. Model limitations and appropriate use cases are communicated to reduce misuse and improve trust.
Auditability & Clinical Governance
Secure logs support review and governance processes, enabling healthcare teams to monitor use and outcomes. This improves accountability and supports responsible deployment in clinical contexts.
Responsible AI Principles (CardioX):
Clinician remains the final decision-maker
Interpretability prioritised over “black box” predictions
Patient confidentiality protected through secure storage
Transparency through evaluation metrics and documented limitations
Clinical Disclaimer:
CardioX is a prototype clinical decision-support system developed for research and educational purposes. It should not be used as a substitute for professional medical judgement in real clinical decision-making.
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