Quantum machine learning predicts radiation esophagitis in cancer patients

Origin Quantum/Origin Wukong-180

Researchers presented a quantum machine learning approach that predicts radiation esophagitis in esophageal cancer patients by combining quantum computing with classical methods. The system converts dose distribution images into quantum states for feature extraction. External validation on 55 patients achieved 83% accuracy, suggesting quantum ML can improve treatment planning and reduce side effects.

• Combines quantum computing with classical machine learning for medical prediction.
• Converts radiation dose distribution images into quantum states for feature analysis.
• Trained on 218 patients with external validation on 55 additional patients.
• Achieved 83% accuracy and AUC of 0.83 in predicting severe radiation esophagitis.