In recent years, machine learning for clinical decision support has gained more and more attention.
no code implementations • 8 Jul 2022 • Roland Roller, Laura Seiffe, Ammer Ayach, Sebastian Möller, Oliver Marten, Michael Mikhailov, Christoph Alt, Danilo Schmidt, Fabian Halleck, Marcel Naik, Wiebke Duettmann, Klemens Budde
However, in the context of clinical text processing the number of accessible datasets is scarce -- and so is the number of existing tools.
This also applies to information about a person's health status.
To detect and use those relevant information, laymen language has to be translated and/or linked against the corresponding medical concept.
We argue that this surprising finding puts results of previous systems and the complexity of recent QA datasets into perspective.
Ranked #6 on Question Answering on NewsQA
In this work we present a fine-grained annotation schema to detect named entities in German clinical data of chronically ill patients with kidney diseases.