student profile: Mr Raquib-ul Alam


Thesis work

Thesis title: Image and signal analysis towards scalable monitoring of brain disease progression and effective treatment

Supervisors: Alistair MCEWAN , Luping ZHOU

Thesis abstract:

�p�In 2018, dementia is estimated to cost Australia about $15 billion. By 2025, the total cost is predicted to increase to $18.7 billion. In a like manner, approximately one in 3,000 Australians are affected by multiple sclerosis (MS) and it is one of the most common causes of chronic neurological disability in adults. These circumstances are, again, similar in developing countries like Bangladesh. Currently, the ability of patients of dementia, MS, pain and clinical depression to track and monitor the progression of their diseases is limited. Traditionally, patients discuss their disease development with their physician a few times a year. This creates low resolution and limited quantified tracking of the disease progression. It has not been tried to analyze combinations of multimodal medical data to track brain disease progression that may result quantified reports. The proposed steps include collecting multimodal medical data from patients, building machine learning (ML) models to find patterns in data and produce useful insights about the disease/treatment, building tools to monitor brain disease progression and treatment efficacy using ML, building cheap solutions so that people from remote areas can be benefited. In short, a better healthcare, primarily for Australians, but also for the rest of the world, should be the result of the research.�/p�

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