Programming Homework Help

Assessment Brief

Lately, deep Learning has a tremendous amount of attention especially in medical image analysis. In
this assignment you will be required to design, develop, analyse and evaluate an appropriate deep
learning model. You can build your own model or use a pretrained model with your layers added to
it. You will explore the dataset and then apply that model to a dataset of your choosing. You will
need to evaluate the performance in terms of precision, recall, F1-score, ROC-curve and PR-curve.
You will discuss the findings that have been produced, and critically reflect upon the model and its
predictions.

The word limit for the report is 2000-2200 words, not including the
front cover, table of contents page, references and appendices.

Assessment Tasks (choose any one of them)

You have been provided with access to three datasets; all are available on Kaggle (Please see links
below). The data covers the following scenarios:

• Classification of blood cell types

• Chest X-ray classification to COVID-19, Viral Pneumonia, normal

• Brain tumour detection from MRI images

You are required to choose one of the above scenarios as your assignment. Your task is to produce a
deep learning model that is appropriate to the problem. The model can be your own model or
designed based on fine-tuning of a pretrained model. You are required to conduct data
preparation/transformation to make the data ready for the model. Please note that what will be
provided in the report should reflect on the python code.

Please also note NOT to take on any
existing code online as your own work.

The errors in the code will affect your mark final mark.
The key components you must complete are:

1. Explore the dataset to understand its characteristics [10 Marks]

2. Pre-process your data to be suitable for building the model [10 Marks]

3. Build the model that allows for the task specified for chosen dataset [20 Marks]

4. Evaluate the model predictions using the metrics stated above. [15 Marks]

5. Fine-tune the model to get better predictions on the test set [15 Marks]

6. Present your findings with suitable visualisations that are easy to interpret [15 Marks]

7. Critically evaluate and discuss the whole process and he findings and what can be improved
[15 Marks}

Please follow the above structure/outline and the Table of contents should be in the bove outline.

Datasets:

1. Blood cells images dataset:https://www.kaggle.com/paultimothymooney/blood-cel…

2. COVID-19 chest X-ray dataset: https://www.kaggle.com/pranavraikokte/covid19-imag…

3. Brain MRI images for brain tumour detection: https://www.kaggle.com/navoneel/brain-mri-images-f…