| KEYWORD |
AI-based Technologies to Understand Clinical Notes
keywords NATURAL LANGUAGE PROCESSING, SUMMARIZATION
Reference persons MAURIZIO MORISIO
External reference persons Giuseppe Rizzo, ISMB
Research Groups GR-16 - SOFTWARE ENGINEERING GROUP - SOFTENG
Thesis type EXPERIMENTAL
Description The digital transformation that healthcare has undergone has encouraged the generation of a large quantity of digital clinical notes. Majority of those notes contain unstructured information which complicates the search, analysis, and the understanding of the content.
The automated analysis and understanding of those notes is of now one of the biggest challenges in healthcare.
In this thesis the undergraduate will study and experiment with AI-based technologies for:
extracting and classify key information such as adverse events from clinical notes written in natural language;
generating a coherent and human-readable summary of a sequence of clinical notes.
The thesis will be structured as follows:
state-of-the-art critical analysis in the field of artificial intelligence applied to healthcare;
problem formulation: objective function, data structures and resources to be used;
algorithm design and prototyping;
in-lab testing verification with real data and measurement of the performance of the approach.
The thesis will be co-tutored with the Institute of Biomedical Engineering, University of Oxford. As the opportunity arises, there could be the possibility of doing this thesis abroad depending on the requirements and plans of the master you’re enrolled in.
Required skills python, java
Deadline 31/01/2019
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