Terra Quantum has developed a groundbreaking hybrid quantum neural community (HQNN) mannequin that outperforms conventional strategies in figuring out wholesome livers appropriate for transplantation. Collaborating with medical specialists, the corporate designed a system combining quantum computing with classical machine studying, reaching a 97% picture classification accuracy for diagnosing non-alcoholic fatty liver illness (NAFLD). This represents a 1.8% enchancment over present strategies.

Revealed within the journal Diagnostics, the examine, titled Hybrid Quantum Image Classification and Federated Learning for Hepatic Steatosis Diagnosis, highlights the potential of HQNNs to supply exact diagnoses whereas defending affected person privateness. The mannequin leverages federated studying, enabling information sharing amongst hospitals with out compromising affected person info, aligning with stringent privateness laws.

This advance may revolutionize liver transplantation by bettering donor liver choice and probably growing transplant charges. The Terra Quantum algorithm not solely enhances diagnostic accuracy but in addition reduces false positives, guaranteeing higher outcomes for sufferers.

Further info will be present in a press launch which will be accessed here.

August 13, 2024