Hospital-wide Natural Language Processing summarising health data of 1 million patients

Supplementary Figures

This page contains an interactive visualisations from the paper "Hospital-wide Natural Language Processing summarising health data of 1 million patients".

• Patient embedding
• Treemap - top 100 concepts and "others" (v1)
• Treemap - top 100 concepts only (v2)

Authors

Daniel Bean, Zeljko Kraljevic, Anthony Shek, James Teo, Richard Dobson

Citation

Preprint available here.

Hospital-wide Natural Language Processing summarising the health data of 1 million patients

Daniel Bean, Zeljko Kraljevic, Anthony Shek, James Teo, Richard Dobson

medRxiv 2022.09.15.22279981; doi: https://doi.org/10.1101/2022.09.15.22279981

Github

Github link

Acknowledgements

This work uses data provided by patients and collected by the NHS as part of their care and support. We would like to thank the patients on the Kings Electronic Records Research Interface (KERRI), the NIHR Applied Research Centre South London, the NIHR Maudsley Biomedical Research Centre, the London AI Centre for Value-based Healthcare, the NHS AI Lab and Health Data Research (UK).

Funding

The project has received funding support from Innovate UK, NHS AI Lab, Office of Life Sciences, Health Data Research UK, NIHR Maudsley Biomedical Research Centre and NIHR Applied Research Centre South London.