AI in Tinnitus (EEG-Based Prediction)
This project uses AI and EEG data to predict individual responses to tinnitus treatment. By analysing brain activity and cognitive measures, the model classifies patients as responders or non-responders with up to 100% accuracy. This supports personalised treatment and potential real-time monitoring.
Project team
- Maryam Doborjeh (AUT)
- Grant Searchfield (University of Auckland)
- Zohreh Doborjeh (AUT)
- Philip Sanders (University of Auckland)
- Grace Y. Wang (University of Southern Queensland)
- Alex Sumich (Nottingham Trent University)
