Thesis Type: Thesis in Computer Science, Data Engineering, Computer Engineering, Mathematical Engineering, Data Science
Research Area: Innovation Development
Requirements
• Experience with Python and/or Java
• Basic knowledge of modular development
• Beginner of (or willing to learn quickly) machine learning
• Curiosity-driven mindset.
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 are enrolled in. The undergraduate will benefit from being immersed in a research environment. It is a unique setting to get into a research mindset with a strong push for innovation. At the end of the thesis, the undergraduate will be familiar with deep learning and semantic analysis, and he will acquire an understanding of the healthcare domain. During the project, he will be able to design and implement an intelligent system applied to real case studies. As additional benefit, she/he will use proficiently control version systems, continuous integration systems, remote deploying and monitoring techniques.
Contact: Send a resume with attached the list of exams to giuseppe.rizzo@linksfoundation.com specifying the thesis code and title.