Health Prediction Using Network Reconstruction Based Model

Complex networks have become indispensable tools for probing complex relationships and interactions across diverse systems. The paper presents an innovative predictive model that utilizes network reconstruction techniques to construct networks from accessible data-sets. The proposed model portrays data features as network nodes, with their interconnections illustrated as edges. Further, a novel methodology is introduced for computing the decision parameter (
$a$
) to forecast an individual's health status.