Private and interpretable clinical prediction with quantum-inspired tensor train models

José Ramón Pareja Monturiol, Juliette Sinnott, Roger G. Melko +1

Publicly available clinical machine learning models pose an underappreciated privacy risk: their parameters or outputs can be exploited to recover information from patients whose d…