Variational Quantum Circuit Topology Grid Search for Hypocalcemia Following Thyroid Surgery

Abstract

Quantum computing’s potential to revolutionise medical applications has spurred interest in leveraging quantum algorithms for healthcare challenges. In this research, the authors explored the application of variational quantum circuits to predicting hypocalcemia risk following thyroid surgery. Hypocalcemia, resulting from hypoparathyroidism, is a common post-surgical complication. This novel approach includes a topology grid search of the variational quantum circuits. To execute the grid search, our research employed a classical optimiser that guided the adjustment of different circuit topologies, assessing their impact on predictive performance. Our research used, as relevant features, an intra-operative PTH (parathyroid hormone) at 10 min post-removal and percentage decrease of pre-operative and intra-operative PTH levels. The findings revealed insights into the interplay between variational quantum circuit topologies and predictive accuracy for hypocalcemia risk assessment.

Keywords

• quantum-inspired algorithms
• neural search architecture
• dense networks
• hypocalcemia