Nilay Khare

LDCML: A Novel AI-Driven Approach form Privacy-Preserving Anonymization of Quasi-Identifiers

2024 · Data & Metadata

Introduction: the exponential growth of data generation has led to an escalating concern for data privacy on a global scale. This work introduces a pioneering approach to address the often overlooked data privacy leakages associated …

Hierarchical federated edge learning with criticality-aware aggregation for privacy-preserving fetal health classification

2026 · Discover Computing

The automated classification of fetal health from cardiotocographic (CTG) recordings is a crucial machine learning application in obstetric diagnostics. Although centralized predictive models have advanced significantly, their large-scale clinical deployment remains structurally constrained by institutional …