{"ID":2858136,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2510.15943","arxiv_id":"2510.15943","title":"Enabling Responsible, Secure and Sustainable Healthcare AI - A Strategic Framework for Clinical and Operational Impact","abstract":"We offer a pragmatic model to operationalize responsible, secure, and sustainable healthcare AI, aligning world-class technical excellence with organizational readiness. The framework includes five key pillars - Leadership \u0026 Strategy, MLOps \u0026 Technical Infrastructure, Governance \u0026 Ethics, Education \u0026 Workforce Development, and Change Management \u0026 Adoption - and is intended to operationalize 'compliance-by-design' while delivering measurable impact. We demonstrate its utility through two deployments. (A) An inpatient length of stay (LOS) prediction service had R^2=0.41-0.58 with validation cohorts in an observational pilot (n = 3,184 encounters, 4 units, June-August 2025). Adoption was 78 percent by week 6, and target units saw 5-10 percent relative declines in mean LOS for complex cases vs. pre-pilot baselines. (B) An AI-augmented radiology second-reader for lung nodules (PACS-integrated with thresholding and explanation overlays) achieved high sensitivity (95 percent) and provided a +8.0 percentage-point lift in detection of sub-centimeter actionable findings, without slowing workflow (median report TAT 23 min, p = 0.64). Both services executed in monitored, auditable pipelines with well-defined rollback, bias checks, and no evidence of security incidents. These findings indicate that by combining strong MLOps and AI security with governance, education, and human-centric change, we can accelerate adoption of AI while improving security and outcomes. We end with limitations, generalization considerations, and a roadmap for scaling across varied clinical and operational use cases.","short_abstract":"We offer a pragmatic model to operationalize responsible, secure, and sustainable healthcare AI, aligning world-class technical excellence with organizational readiness. The framework includes five key pillars - Leadership \u0026 Strategy, MLOps \u0026 Technical Infrastructure, Governance \u0026 Ethics, Education \u0026 Workforce Developm...","url_abs":"https://arxiv.org/abs/2510.15943","url_pdf":"https://arxiv.org/pdf/2510.15943v1","authors":"[\"Jimmy Joseph\"]","published":"2025-10-09T12:40:59Z","proceeding":"cs.CY","tasks":"[\"cs.CY\"]","methods":"[\"Generative Adversarial Network\"]","has_code":false}