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Shiren
Patel
Head of Innovation Technology and Data Research
Great Ormond Street Hospital
Shiren joined DRIVE in 2022 as the Innovation Technology Consultant to facilitate implementation and provide direction for DRIVE’s Data and Digital Strategies. In September 2023, Shiren took on the additional role of Interim Head of the Digital Research Environment (DRE). Shiren is responsible for setting the DRE strategy to leverage multimodal data with cutting-edge AI techniques, adhering to best practices in software engineering and Reproducible Analytical Pipelines (RAP). This strategy fosters expansion of data, platforms, and applications, including federated analytics, which will fuel collaborative efforts and advanced research in paediatric diagnosis, treatment, and care. Shiren initially joined GOSH in 2021 as the Head of Enterprise Applications and has extensive experience in IT and digital infrastructure roles within the NHS.
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07 November 2024 14:30 - 15:00
Large language models in practice: Insights from building LLM-based pipelines for paediatric healthcare data
In this keynote, our speakers will provide an overview of the GOSH DRIVE team’s journey towards leveraging the capabilities of AI technologies to enrich our data resources. We will then focus on the potential capabilities of Large Language Models (LLMs) within the paediatric healthcare setting. Large volumes of data are recorded as part of routine healthcare, but often much of this data remains unused for the purposes of research and developing our capabilities as it is simply not feasible to manually extract all the data. In this session we will discuss how we have been able to perform high quality, reliable and accurate data extraction from documents, by leveraging the power of LLMs. We will share our experience and insights towards deploying "smaller" general-purpose LLMs for extracting relevant information that is present within unstructured texts and their enhanced zero-shot capabilities with the help of hand-crafted prompts. We will also share generalisability across a number of use-cases.