View Proposal

---

Proposer

Marta Vallejo

Title

Detecting COVID-19 Through Tongue Image Analysis Using Advanced Neural Networks

Goal

This project objectives aim to contribute to the early detection of COVID-19 through non-invasive tongue image analysis, potentially aiding in the timely management and control of the disease.

Description

COVID-19 is an infectious disease that typically presents with mild to moderate respiratory symptoms that, in severe cases, can lead to pneumonia or even death. This underscores the critical importance of non-invasive, cheap early detection methods. In a previous project, the YOLOv8 neural model was trained with real tongue images captured by clinicians using smartphones. The aim was to register the area of interest and standardise the dataset using semi-supervised learning techniques. A very basic convolutional neural network was implemented, yielding promising initial results. Project Objectives: Based on last year's outcomes, the extension of this project includes the following key objectives: 1.- Final Model Implementation: Develop and implement the final classification model(s) to evaluate the suitability and performance of the dataset. 2.- Data Augmentation Techniques: Create and apply relevant data augmentation techniques to enhance the robustness of the model and ensure a balanced dataset. Optional Enhancements: 3.- Registration Model Improvement: Refine the existing registration model to increase accuracy. 4.- Front-End Application Development: Design and implement a user-friendly front-end application to facilitate the use of the model in real-world scenarios. If the output of the project is satisfactory, it is encouraged to publish the results in a journal or conference paper. This project is in collaboration with Dr Fernando Auat (ISSS/EPS).

Resources

A real clinical pre-processed dataset.

Background

Python programming, interest in machine learning, deep learning and healthcare applications.

Url

Difficulty Level

High

Ethical Approval

Full

Number Of Students

2

Supervisor

Marta Vallejo

Keywords

machine learning, deep learning, medical imagen, segmentation, data augmentation

Degrees

Bachelor of Science in Computer Science
Master of Engineering in Software Engineering
Master of Science in Artificial Intelligence
Master of Science in Artificial Intelligence with SMI
Master of Science in Computing (2 Years)
Master of Science in Data Science
Master of Science in Software Engineering
Bachelor of Science in Computing Science
Postgraduate Diploma in Artificial Intelligence
Bachelor of Science in Statistical Data Science
BSc Data Sciences