Antiepileptic drug is the mainstay of treatment modality for epilepsy. People with epilepsy often require lifelong antiepileptic drug treatment. Previous Glasgow study in 2000 demonstrated a-third of the epilepsy patient did not response well to antiepileptic drug therapy. Despite the introduction of more than a dozen new antiepileptic drugs in the past two decades, there remain no robust data to suggest improvement in treatment outcomes in the recent expanded Glasgow study. To valid the prognosis and antiepileptic drug response patterns observed in the Glasgow studies. We will assess treatment outcomes of newly treated epilepsy patients who were seen at a First Seizure Clinic and were prospectively followed up in Australia. We will extract seizure, diagnostic and treatment information from baseline and follow-up clinical documents and construct a digital database. Various methods will be used in modelling treatment outcomes including traditional statistical methods and advanced machine learning approaches. This project is suitable for students with biostatistics and/or computer science background.
Statistics, computer science, machine learning, artificial intelligence, Antiepilpetic Drug, Newly Diagnosed, Newly Treated, Seizure-free, Epilepsyl, physiology, pharmacology, microbiology, anatomy, developmental biology, molecular biology, biochemistry, immunology, human pathology, clinical
Central Clinical School » Neuroscience
Masters by research
Masters by coursework
Top-up scholarship funding available
Alfred Research Alliance