AIMC Topic: Data Curation

Clear Filters Showing 51 to 60 of 147 articles

Using FHIR to Construct a Corpus of Clinical Questions Annotated with Logical Forms and Answers.

AMIA ... Annual Symposium proceedings. AMIA Symposium
This paper describes a novel technique for annotating logical forms and answers for clinical questions by utilizing Fast Healthcare Interoperability Resources (FHIR). Such annotations are widely used in building the semantic parsing models (which aim...

Label Co-Occurrence Learning With Graph Convolutional Networks for Multi-Label Chest X-Ray Image Classification.

IEEE journal of biomedical and health informatics
Existing multi-label medical image learning tasks generally contain rich relationship information among pathologies such as label co-occurrence and interdependency, which is of great importance for assisting in clinical diagnosis and can be represent...

PGxCorpus, a manually annotated corpus for pharmacogenomics.

Scientific data
Pharmacogenomics (PGx) studies how individual gene variations impact drug response phenotypes, which makes PGx-related knowledge a key component towards precision medicine. A significant part of the state-of-the-art knowledge in PGx is accumulated in...

Improving clinical named entity recognition in Chinese using the graphical and phonetic feature.

BMC medical informatics and decision making
BACKGROUND: Clinical Named Entity Recognition is to find the name of diseases, body parts and other related terms from the given text. Because Chinese language is quite different with English language, the machine cannot simply get the graphical and ...

An interpretable natural language processing system for written medical examination assessment.

Journal of biomedical informatics
OBJECTIVE: The assessment of written medical examinations is a tedious and expensive process, requiring significant amounts of time from medical experts. Our objective was to develop a natural language processing (NLP) system that can expedite the as...

Using distant supervision to augment manually annotated data for relation extraction.

PloS one
Significant progress has been made in applying deep learning on natural language processing tasks recently. However, deep learning models typically require a large amount of annotated training data while often only small labeled datasets are availabl...

Phenotype annotation with the ontology of microbial phenotypes (OMP).

Journal of biomedical semantics
BACKGROUND: Microbial genetics has formed a foundation for understanding many aspects of biology. Systematic annotation that supports computational data mining should reveal further insights for microbes, microbiomes, and conserved functions beyond m...

Detecting Mistakes in CPR Training with Multimodal Data and Neural Networks.

Sensors (Basel, Switzerland)
This study investigated to what extent multimodal data can be used to detect mistakes during Cardiopulmonary Resuscitation (CPR) training. We complemented the Laerdal QCPR ResusciAnne manikin with the Multimodal Tutor for CPR, a multi-sensor system c...

Domain transformation on biological event extraction by learning methods.

Journal of biomedical informatics
Event extraction and annotation has become a significant focus of recent efforts in biological text mining and information extraction (IE). However, event extraction, event annotation methods, and resources have so far focused almost exclusively on a...

Toward automatic prediction of EGFR mutation status in pulmonary adenocarcinoma with 3D deep learning.

Cancer medicine
To develop a deep learning system based on 3D convolutional neural networks (CNNs), and to automatically predict EGFR-mutant pulmonary adenocarcinoma in CT images. A dataset of 579 nodules with EGFR mutation status labels of mutant (Mut) or wild-type...