Hybrid Quantum-Classical Machine Learning for COVID-19
quantum machine learning
classification
A quantum-classical classifier using amplitude embedding and transfer learning.
This project classified COVID-19 cases from clinical features such as hematocrit, hemoglobin, platelets, red blood cells, lymphocytes, and MCHC. The pipeline embedded classical data into quantum states and used a hybrid quantum-classical model for classification.