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Application of machine learning methods to diagnosis of neurological disorders from medical records

Description 
Diagnosis of patients with neurological disorders such as stroke and non-stroke, seizure or no seizure and multiple sclerosis can be difficult for non-neurologists. Improving diagnosis can help health care workers to expedite care. In this study, we plan to use supervised machine learning approach to compare models for classifying patients presenting to emergency department or outpatient clinics with potential neurological disorders..
Essential criteria: 
Minimum entry requirements can be found here: https://www.monash.edu/admissions/entry-requirements/minimum
Keywords 
stroke, epilepsy, multiple sclerosis, dementia
School 
School of Clinical Sciences at Monash Health / Hudson Institute of Medical Research
Available options 
PhD/Doctorate
Honours
BMedSc(Hons)
Time commitment 
Full-time
Part-time
Top-up scholarship funding available 
No
Physical location 
Monash Medical Centre Clayton
Co-supervisors 
Assoc Prof 
Henry Ma
Assoc Prof 
Udaya Seneviratne

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