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@article{201818,
        author = {Ravina and Gopal Khorwal},
        title = {Reframing Ethical Accountability in AI-Driven Healthcare: A Lifecycle-Based Multidimensional Framework},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {12},
        pages = {5495-5499},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=201818},
        abstract = {Artificial Intelligence (AI) is increasingly integrated into healthcare systems, offering significant advancements in diagnostics, predictive modeling, and personalized treatment. Despite its potential, ethical concerns related to bias, transparency, accountability, and privacy continue to limit its responsible adoption. This study presents a lifecycle-based ethical framework for evaluating AI systems in healthcare. A mixed-method approach combining literature synthesis, algorithmic auditing, and clinical simulation was employed. The findings indicate that ethical risks are highest during data collection and preprocessing, while explainable AI significantly improves clinician trust. The framework integrates ethical principles across all lifecycle stages, enabling continuous monitoring and governance. This research provides a practical model for ethically aligned AI deployment and contributes to the development of trustworthy healthcare technologies.},
        keywords = {},
        month = {May},
        }