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Aims:

The module aims to enable you to accumulate work experience in AI on a real-world problem within the biomedical application realm from diagnosis and disease prognosis to clinical services workflow delivery.Ìý

The aims are to:Ìý

• Provide students the opportunity to apply learned machine learning and artificial intelligence methodologies to the biomedical and healthcare domain.ÌýÌý
• Capacitate students to propose and design ML and AI solutions to solve specific real problems in the biomedical and healthcare field.Ìý
• Capacitate students to be effective team players in interdisciplinary research groups within the biomedical and clinical sciences.

Intended learning outcomes:

On successful completion of the module, a student will be able to:Ìý

1. Assimilate the project-specific biomedical terminology, its relation to clinical pathways and the challenges in clinical decision support.Ìý

2. Design, implement and evaluate AI and ML algorithms to solve real-world clinical problems.Ìý

3. Interpret and analyse the challenges of healthcare datasets.Ìý

4. Evaluate the ethical implications of using AI to improve healthcare.

Indicative content:

The following are indicative of the topics the module will typically cover:

This three-month individual-project structure is aimed to consolidate our students’ knowledge in Artificial Intelligence (AI) and Machine Learning (ML), acquired during first and second terms of the programme, by immersing them within the biomedicine and healthcare domain environment.ÌýÌý

Students will learn how to apply their acquired knowledge to design, implement and evaluate an AI solution to attempt to solve a real biomedical and healthcare challenge.ÌýÌý

Requisites:

To be eligible to select this module as an optional or elective, a student must be registered on a programme and year of study for which it is formally available.