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Machine Learning for Chronic-Stress Symptoms in Preclinical Studies

Augments automated mouse-behaviour analysis with EEG neurophysiology, learning combined representations to identify stress phenotypes and evaluate pharmacological interventions.

  • ML
  • EEG
  • Behavioural analysis
  • Preclinical
  • Healthcare
Machine Learning for Chronic-Stress Symptoms in Preclinical Studies
Status
Active
Sponsor
Ministry of Science and Higher Education (Poland)
Duration
01 Oct 2024 - 30 Sept 2028
PWr budget
MNiSW · Implementation PhD II (Artificial Intelligence & Quantum Technologies) · 387,222 PLN

Develops machine-learning approaches that combine non-invasive EEG signals with discrete behavioural symptoms in preclinical models. Outputs include a phenotyping platform serving both academic research and commercial applications.