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Md Sibbir Hossain

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Open access Aug 2026

Safeguarding Public Healthcare Spending with Explainable AI: A Statistically Validated Machine Learning Framework for Medicaid Fraud Detection and Electronic Visit Verification

Overall, the findings demonstrate that a compact, explainable, and statistically validated machine learning framework can achieve strong, stable, and computationally efficient fraud discrimination, providing a methodologically sound foundation for extending claims-based fraud analytics into real-time, EVV-integrated Me...

Md Sibbir Hossain, A. T. M. Fokrule Hasan · 0 citations
#explainable ai Open access Aug 2026

Auditable Credit Risk Intelligence for the U.S. Financial System: A Scalable Explainable-AI Framework Reconciling Predictive Performance with ECOA, FCRA, and Model Risk Governance

Machine-learning credit underwriting in the United States operates under three families of obligation that are not reducible to one another: a statutory prohibition on discrimination, a statutory duty to disclose the specific principal reasons for an adverse action, and prudential expectations for model risk management...

Hasibur Rahman, Sarder Abdulla Al Shiam, Md Sibbir Hossain · 0 citations

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