Recent advances in biomedical literature mining
The recent years have witnessed a rapid increase in the number of scientific articles in
biomedical domain. These literature are mostly available and readily accessible in …
biomedical domain. These literature are mostly available and readily accessible in …
ChemDataExtractor: a toolkit for automated extraction of chemical information from the scientific literature
The emergence of “big data” initiatives has led to the need for tools that can automatically
extract valuable chemical information from large volumes of unstructured data, such as the …
extract valuable chemical information from large volumes of unstructured data, such as the …
Text mining resources for the life sciences
Text mining is a powerful technology for quickly distilling key information from vast quantities
of biomedical literature. However, to harness this power the researcher must be well versed …
of biomedical literature. However, to harness this power the researcher must be well versed …
A global network of biomedical relationships derived from text
Motivation The biomedical community's collective understanding of how chemicals, genes
and phenotypes interact is distributed across the text of over 24 million research articles …
and phenotypes interact is distributed across the text of over 24 million research articles …
LION LBD: a literature-based discovery system for cancer biology
Motivation The overwhelming size and rapid growth of the biomedical literature make it
impossible for scientists to read all studies related to their work, potentially leading to missed …
impossible for scientists to read all studies related to their work, potentially leading to missed …
Knowledge-based extraction of adverse drug events from biomedical text
Background Many biomedical relation extraction systems are machine-learning based and
have to be trained on large annotated corpora that are expensive and cumbersome to …
have to be trained on large annotated corpora that are expensive and cumbersome to …
Multi-head CRF classifier for biomedical multi-class named entity recognition on Spanish clinical notes
The identification of medical concepts from clinical narratives has a large interest in the
biomedical scientific community due to its importance in treatment improvements or drug …
biomedical scientific community due to its importance in treatment improvements or drug …
Enhancing timeliness of drug overdose mortality surveillance: A machine learning approach
Background Timely data is key to effective public health responses to epidemics. Drug
overdose deaths are identified in surveillance systems through ICD-10 codes present on …
overdose deaths are identified in surveillance systems through ICD-10 codes present on …
RENET2: high-performance full-text gene–disease relation extraction with iterative training data expansion
Relation extraction (RE) is a fundamental task for extracting gene–disease associations from
biomedical text. Many state-of-the-art tools have limited capacity, as they can extract gene …
biomedical text. Many state-of-the-art tools have limited capacity, as they can extract gene …
[HTML][HTML] A quantitative and qualitative evaluation of sentence boundary detection for the clinical domain
Sentence boundary detection (SBD) is a critical preprocessing task for many natural
language processing (NLP) applications. However, there has been little work on evaluating …
language processing (NLP) applications. However, there has been little work on evaluating …