AWS re:Invent 2024 - Improving patient care with large-scale data engineering and ML (PRO207)

Since over 80% of healthcare data is unstructured, applying traditional machine learning (ML) approaches to healthcare data poses a significant challenge. In this lightning talk, learn how to implement Amazon Bedrock, Amazon Textract, and other AWS native services to efficiently process unstructured medical document data and train ML models to inform clinical decision-making. Discover how to build a solution that combines large-scale data engineering, large language model–driven document extraction and understanding, and ML training to process documents, generate structured data models informed by clinical subject matter experts, and evaluate ML model performance.

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