CogStack speaking at NVIDIA GTC – Organizing, Structuring, and Utilizing the Vast Amount of Clinical Information Available in Electronic Health Records

[vc_row css=”.vc_custom_1534419916692{padding-bottom: 5px !important;}”][vc_column][vc_column_text]Learn how CogStack-MedCAT, an open-source natural language processing platform, is used to unlock knowledge available in electronic health records (EHRs) and provide the groundwork for a multitude of downstream medical applications. In-hospital patient data are rarely structured and easily accessible. To facilitate R&D we present CogStack, a data-ingestion and harmonization pipeline used to organize, link, and index multi-source hospital data. As ~80% of EHR data are noisy, ambiguous free text, we present MedCAT, a named-entity recognition and linking tool able to extract and contextualize biomedical concepts from free text. Finally, we’ll present research and applications enabled by CogStack-MedCAT — (1) Multi-hospital COVID-19 projects, and (2) initial results of two novel health-care applications: (a) a self-supervised approach based on language models for temporal modeling of patients and diseases, and (b) a prototype summarization model generating phenotypically accurate, coherent clinical text.
Read more on NVIDIA GTC.[/vc_column_text][vc_column_text]Photo credit: NVIDIA GTC.[/vc_column_text][/vc_column][/vc_row]

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