Dataset and Code for Quantum-AI Enhanced Biosensor for Environmental Toxin Detection: A Synthetic Data Approach

This repository contains the datasets, code, and supplementary figures for the study "Quantum-AI Enhanced Biosensor for Environmental Toxin Detection: A Synthetic Data Approach". The study presents a quantum-AI enhanced biosensor that leverages synthetic data generated via Qiskit’s Aer simulator to classify five environmental toxin classes (control, lead, mercury, cadmium, arsenic) with high accuracy (up to 96.04%). For more details, see the README.md file in the repository.