London School of Hygiene & Tropical Medicine

This module will introduce students to key principles and applications of artificial intelligence (AI) in health and healthcare and equip them with knowledge and skills to critically appraise and plan research around AI in health and healthcare. 

Intended learning outcomes

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

1. At a conceptual level, reflect on the fundamentals of how major classes of AI models work (machine learning (ML), deep learning (DL) and large language models (LLMs), contextualising this within their applications to healthcare.
2. Analyse applications of AI in health and healthcare, explaining how different methods (ML, DL, LLMs) are suited to address diverse clinical and public health problems.
3. Critically appraise research around AI in health and healthcare, evaluating study design, data quality, model development, validation and clinical relevance. 
4. Develop an evaluation plan for an AI-enabled health tool, assessing performance, generalisability, alignment with clinical needs, bias and fairness across diverse populations.
5. Assess governance, ethical, sustainability, and implementation challenges in AI enabled healthcare, proposing practical strategies for responsible and equitable use.

Mode of delivery

This module is delivered predominantly face-to-face. Where specific teaching methods (lectures, seminars, discussion groups) are noted in this module specification these will be delivered by predominantly face-to-face sessions. There will be a combination of live and interactive activities (synchronous learning) as well as self-directed study (asynchronous learning).

Assessment

This will consist of a written report of no more than 1500 words, to be handed in on the final day of the module. Students will be given a summary of a recent paper presenting an AI solution and tasked to prepare a report to a public health manager a) advising them on readiness to adopt this AI-based solution in a given health system context, and b) proposing a study that could be conducted to address one of the readiness challenges identified. The grade for the summative assessment only will go towards the overall award GPA.

Credits

• CATS: 15
• ECTS: 7.5

Module specification

For full information regarding this module please see the module specification.