Adaptive Liquid State-Space Networks: A Novel Neuro-Dynamic Architecture for Tabular Classification with Application to Anemia Diagnosis

Background/Objectives: Anemia is a complex hematological disorder with various subtypes, and its accurate diagnosis is of critical importance for clinical decision-making processes. Traditional machine learning algorithms and standard deep learning models often struggle to model the nonlinear and typically imbalanced nature of clinical tabular data, which negatively impacts the classification performance and reliability of diagnostic systems.

Methods