Bias in healthcare data can have serious consequences, impacting diagnoses, treatments, and overall patient outcomes. Dr Julia Ive dives deep in this critical issue, exploring the potential of Artificial Intelligence (AI) to analyse the qualitative aspects of healthcare records, specifically through Natural Language Processing (NLP).
11 July 2024 How can we reduce bias in healthcare data?
It’s a complex, multifaceted question. One that requires us to think not just about quantitative data and trends, but about the language used by doctors and nurses across the country to describe, diagnose, and evaluate conditions from oncological cancers to paediatric anxiety.
My research looks into what role AI can play in tackling this need for large-scale qualitative analysis through Natural Language Processing (NLP) programs.
You may have already noticed how artificial intelligence tools are proliferating the consumer market with generative-AI tools such as ChatGPT. Recently however, research into large language models is helping extend the capabilities of AI across sectors, including the large-scale analysis of patient records. This is raising debate around data privacy, the accuracy of neural networks, and the role of AI in public health. When it comes to our nation’s health, understandably there is a pressing need to ensure any tool that is rolled out is done so in a safe and comprehensive fashion.
The benefits are great, but to achieve them we must ensure we understand the uses of AI in healthcare, and how we can mitigate any risks. So how can we use NLP programs to overcome bias in health records and better treat conditions such as paediatric anxiety.
New voices in healthcare
AI has a unique ability to analyse complex data at a large scale. This especially concerns textual data such as mental health records which contain significant amounts of detail that can be difficult for humans to aggregate and identify trends.
Mental health notes are written qualitatively, so there is no objective method to describe the complex and varied symptoms of mental health conditions.We’re using AI to address this by employing NLP programs called Transformers. Where less sophisticated tools struggle with the context and complexity of written language, Transformers have […]
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