Tools and technology for curating biomedical knowledge
Given the ever-growing medical knowledge, the creation of an AI-based curation tool is critical to providing competitive, knowledge-based medical applications in the future.
The key to this is to use a combination of natural language processing, semantic resources, and AI tailored to the specificities of biomedicine with the goal of translating potentially relevant information into a machine-readable knowledge structure. In this talk, we present tools, strategies and resources created at Ada Health GmbH to tackle this challenging task.
Dr. Sarah Schulz
Dr. Sarah Schulz has a background in natural language processing (NLP). She has worked in the field of Digital Humanities during her time as a PhD student. Her main interest is the processing of language that deviates from newspaper which has been the focus of NLP in its early stage. Digital Humanities projects often include such texts. She especially enjoys that these projects have specific questions towards texts. She is fascinated by the interaction between texts with very specific characteristics which often make automated approaches difficult and the specificity of research questions which in turn facilitate the processing.
Currently, she is working as an NLP research engineer at Ada Health in Berlin where she tries to get a handle on the pitfalls of medical language processing.