Discovering diabetes and related pathologies through learning approaches using electronic health records (EHRs)

Degree Course: 
Biomedical/Electronic/Computer science engineer (Information-engineering track)
Department of Information Engineering - UNIVPM

Diabetes mellitus (DM), commonly referred to as diabetes, is a group of metabolic disorders in which there are high blood sugar levels over a prolonged period. Symptoms of high blood sugar include frequent urination, increased thirst, and increased hunger. The goal of this thesis is to exploit electronic health records (EHRs) to provide DM and related pathologies (i.e., cardiovascular diseases) diagnosis. The main challenges are identifying EHR meaningful features and to provide robust diagnosis. In this context, the candidate will be required to study, investigate and apply machine-learning approaches for data-driven diagnosis of DM.

Aim: Applying machine learning and deep learning for the diagnosis of diabetes mellitus diabetes

Supervisors: Luca Romeo, Sara Moccia, Michele Bernardini

Start: Sept, 2018

Expected graduation: Feb/July, 2019

Skills that will be acquired: Programming (Python, MATLAB)

Contacts: {e.frontoni, l.romeo, s.moccia}

Academic Tutor: 
Emanuele Frontoni