• Publications
  • Influence
Clinical Natural Language Processing in languages other than English: opportunities and challenges
TLDR
This paper offers the first broad overview of clinical Natural Language Processing (NLP) for languages other than English and identifies major challenges and opportunities that will affect the impact of NLP on clinical practice and public health studies in a context that encompasses English as well as other languages.
Stockholm EPR Corpus : A Clinical Database Used to Improve Health Care
TLDR
A number of possible applications are described, including comorbidity networks, detection of hospital-acquired infections and adverse drug reactions, as well as diagnosis coding support.
Improving Precision in Information Retrieval for Swedish using Stemming
TLDR
An evaluation of how much stemming improves precision in information retrieval for Swedish texts by building an information retrieval tool with optional stemming and creating a tagged corpus in Swedish found that stemming improved both precision and recall.
Clinical Text Mining
  • H. Dalianis
  • Computer Science
    Springer International Publishing
  • 2018
Recent Advances in Clinical Natural Language Processing in Support of Semantic Analysis.
TLDR
There has been an increase of advances within key NLP subtasks that support semantic analysis, and a reflection upon most recent developments and potential areas of future NLP development and applications is provided.
Automatic training of lemmatization rules that handle morphological changes in pre-, in- and suffixes alike
We propose a method to automatically train lemmatization rules that handle prefix, infix and suffix changes to generate the lemma from the full form of a word. We explain how the lemmatization rules
Aggregation in Natural Language Generation
TLDR
This paper identifies and describes the aggregation processes generators can use to remove redundancy in text generation, and defines and describes eight aggregation strategies they identified.
Evaluation Metrics and Evaluation
This chapter describes the metrics for the evaluation of information retrieval and natural language processing systems, the annotation techniques and evaluation metrics and the concepts of training,
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