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How to Build a Foundation of AI-based Healthcare Systems Through Language Models?

Language models with transformer such as BERT and GPT-3 have been successfully outperforming on a variety of Natural Language Processing (NLP) tasks, such as information extraction, text classification, sentence similarity, text generation, text summarization, and question answering.

In this talk, I will review the state-of-the-art open-source tools based on pre-trained language models that can be utilized to build a foundation of an AI-based healthcare system. The tools can be used in medical practice management (MPM) or electronic health records (EHR) management software.

I will review the architecture of each tool, usage, capabilities, and limitations. I will also show case usage and limitation of each tool through a set of demos.

Natural Language Processing for Clinical Excellence: The State of Practices, Opportunities, and Challenges

Rapid growth in the adoption of electronic health records (EHRs) has led to an unprecedented expansion in the availability of large longitudinal...