ENSURING SAFETY, QUALITY, AND TRUST: A HOLISTIC FRAMEWORK FOR RESPONSIBLE AI IN HEALTHCARE
Keywords:
Artificial Intelligence, Healthcare, Safety, Governance, TrustAbstract
Artificial intelligence (AI) is rapidly transforming the healthcare landscape, offering immense potential for improving patient outcomes, enhancing clinical decision-making, and advancing medical research. However, the integration of AI in healthcare also raises critical challenges and risks that must be addressed to ensure safety, quality, and ethical implementation. This comprehensive paper delves into the best practices for developing and deploying AI systems in healthcare, spanning data quality and management, algorithm development and validation, deployment and monitoring, as well as governance and ethical considerations. Key topics explored include mitigating biases in training data, ensuring transparency and interpretability of AI models, protecting patient privacy and data security, and upholding ethical principles such as fairness, accountability, and respect for human autonomy. The paper emphasizes the importance of rigorous testing, validation, and continuous monitoring of AI systems, as well as the need for multidisciplinary collaboration among AI researchers, healthcare professionals, ethicists, and policymakers. Additionally, the paper outlines strategies for incident response, stakeholder engagement, and public education to build trust and informed decision-making around AI in healthcare. With a focus on developing robust, interpretable, and trustworthy AI models, the paper aims to advance the responsible integration of AI technologies in healthcare while addressing ongoing challenges and paving the way for future research and innovation in this rapidly evolving field.
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Copyright (c) 2024 Ramakrishnan Neelakandan, Vidhya Sankaran (Author)
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