Biomedical Text Mining: State-of-the-Art, Open Problems and Future Challenges

Biomedical Text Mining: State-of-the-Art, Open Problems and Future Challenges

Item
http://www.wikidata.org/entity/Q56991858
Interactive machine learning for health informatics: when do we need the human-in-the-loop?Text mining for identifying topics in the literatures about adolescent substance use and depressionMicrobial phenomics information extractor (MicroPIE): a natural language processing tool for the automated acquisition of prokaryotic phenotypic characters from text sourcesAn adaptive annotation approach for biomedical entity and relation recognition.Revealing topics and their evolution in biomedical literature using Bio-DTM: a case study of ginseng.A Pilot Study of Biomedical Text Comprehension using an Attention-Based Deep Neural Reader: Design and Experimental Analysis.Probabilistic Logic Programming in ActionIntegrating Open Data on Cancer in Support to Tumor Growth AnalysisMachine Learning for Health Informatics
P2860

Biomedical Text Mining: State-of-the-Art, Open Problems and Future Challenges

Item
http://www.wikidata.org/entity/Q56991858
description
wetenschappelijk artikel
@nl
наукова стаття, опублікована у 2014
@uk
name
Biomedical Text Mining: State-of-the-Art, Open Problems and Future Challenges
@en
Biomedical Text Mining: State-of-the-Art, Open Problems and Future Challenges
@nl
type
label
Biomedical Text Mining: State-of-the-Art, Open Problems and Future Challenges
@en
Biomedical Text Mining: State-of-the-Art, Open Problems and Future Challenges
@nl
prefLabel
Biomedical Text Mining: State-of-the-Art, Open Problems and Future Challenges
@en
Biomedical Text Mining: State-of-the-Art, Open Problems and Future Challenges
@nl
P1433
P1476
P2093
P2860
P304
P31
P356
P407
P50
P577
P356
P1433
P1476
Biomedical Text Mining: State-of-the-Art, Open Problems and Future Challenges
@en
P2093
P2860
P304
P31
P356
10.1007/978-3-662-43968-5_16
P407
P50
P577