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dc.contributor.authorSalmeron, Jose L.
dc.contributor.authorFernández-Palop, Isabel
dc.date.accessioned2024-04-10T01:02:50Z
dc.date.available2024-04-10T01:02:50Z
dc.date.issued2023
dc.identifier10.3390/math11173659
dc.identifier.issn22277390
dc.identifier.urihttps://hdl.handle.net/20.500.12728/10556
dc.description.abstractQuantum 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. © 2023 by the authors.es_ES
dc.language.isoenes_ES
dc.publisherMultidisciplinary Digital Publishing Institute (MDPI)es_ES
dc.subjectdense networkses_ES
dc.subjecthypocalcemiaes_ES
dc.subjectneural search architecturees_ES
dc.subjectquantum-inspired algorithmses_ES
dc.titleVariational Quantum Circuit Topology Grid Search for Hypocalcemia Following Thyroid Surgeryes_ES
dc.typeArticlees_ES


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