Quantum inspired machine learning is a practical solution to incorporate the effects of quantum algorithms into existing machine learning workflows with classical bit based quantum simulators. Utilizing pure states, exact expectation values, and adjoint differentiation: Circuits consisting of trainable quantum parameters are optimized alongside trainable classical parameters in existing Python/PyTorch notebooks.
Here, the Huynh, L., et al. 2023 'Quantum-Inspired Machine Learning: a Survey' will be analyzed with insight into Quantum "Q" versions vs. existing Classical models for Medical applications.