AI Expert Reveals the Importance of Quality Data in Healthcare Innovation
Artificial intelligence (AI) has the potential to revolutionize healthcare, but only if it is fueled by high-quality data. This was the key takeaway from a recent panel discussion at the London Business School’s think ahead event, titled ‘How Will AI Innovation in Healthcare Improve Our Lives?’
The panel, which included AI expert Barbara Domayne-Hayman, Chief Medical Officer Andrew Vallance-Owen, Professor Nicos Savva, and Senior Director Crystal Ruff, explored the challenges and opportunities of AI in healthcare. Domayne-Hayman highlighted the importance of quality data, specifically in health-related AI, as it affects the accuracy and reliability of AI systems.
She emphasized that the quality of data depends on how it was collected, stored, and analyzed, as well as the representativeness of the samples used. Historically, clinical trials have primarily focused on men within a certain age range, which introduces biases and limits the diversity of data available.
Savva echoed Domayne-Hayman’s observations and stressed the need for understanding the limitations of imperfect data. He suggested documenting the data collection and generation process and addressing any imperfections during model training. By recognizing the boundaries of the model, researchers can better interpret its predictions and overcome data limitations.
Vallance-Owen discussed the importance of building trust in healthcare AI through greater data transparency. He proposed that models should clearly describe their data sources, which is not currently being done. Additionally, he emphasized the need to improve representation and reduce bias in training data, as much of the research is skewed towards North American and European populations.
Ruff highlighted the key risk of data security and sharing in AI healthcare settings. She mentioned the emergence of federated data systems that allow data to be stored securely in different locations while still being accessible and queryable. This innovative approach maintains country-level governance while facilitating collaboration and data sharing.
The panel discussion attracted 600 viewers and was part of a series of events organized by the London Business School. The next event, ‘The Road to COP28 – Aligning Expectations with Actions,’ will take place on November 16, 2023.
This thought-provoking discussion reminds us that AI in healthcare depends on high-quality data. As we embrace the potential of AI to transform healthcare, it is crucial to address issues of data quality, representation, bias, and security. What do you think about the role of data in AI innovation in healthcare? Share your thoughts and join the conversation below!
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