Maksim Belousov

I am a PhD Computer Science student at University of Manchester working on healthcare text analytics. In particular, my current work is focused on researching text mining and classification methods to analyse patients’ experience of drug exposure in social media and measure the severity of adverse drug events and their impact on the quality of life.
My research interests are centred around Natural Language Processing, Machine Learning and Data Mining.
Currently, I am member of Text Extraction, Analytics and Mining Group and UK Healthcare Text Analytics Research Network.

Natural Language Processing

Deriving meaning from human language, including sentiment analysis, named-entity recognition and text classification.

Learning From Data

Getting insights from data, extracting patterns and informative features to make automatic predictions.

Data Visualisation

Developing interactive dashboards and generating visual reports to help researchers perform data analysis.


Analysing patients' experience in social media

Developing text mining pipeline to automatically derive sufficient context from social media to evaluate the severity of adverse drug events and their impact on the quality of patients life.

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Annotating patients' experience

Mining auditory hallucinations from Twitter

An interdisciplinary collaboration of School of Computer Science and School of Psychology aimed to establish the feasibility of harvesting and mining datasets from unsolicited Twitter posts to identify potential auditory hallucinations.

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