Foreword to the third International Symposium for Semantic Mining in Biomedicine
نویسنده
چکیده
Natural Language Processing (NLP) has been active in the medical domain for more than thirty years, with pioneering projects such as the Linguistic String Project. ‘BioNLP’, the application of Natural Language Processing methods to the analysis of the biological literature in the genomics era, has undergone a fast development in little over ten years.1 It rapidly attracted Medical NLP and Computational Linguistics researchers, especially through challenges and evaluation initiatives. We examine here to which extent medical NLP prepared the ground for BioNLP. Conversely, we study the ways BioNLP influenced the practice of medical NLP. 1 Medical NLP: Specificities and Contributions to BioNLP A growing community of researchers applies NLP to the medical domain and develops new methods for that purpose. Medical NLP has seen important breakthroughs, such as routine, machine analysis of clinical reports (MedLEE), but it is probably fair to say that it has had until now only a moderate direct impact on clinical applications. It has been mostly concerned with the clinical domain (clinical notes, etc.), but also with the analysis of the scientific literature (MEDLINE titles and abstracts).
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