Substituting clinical features using synthetic medical phrases: Medical text data augmentation techniques
Biomedical natural language processing (NLP) has an important role in extracting
consequential information in medical discharge notes. Detecting meaningful features from …
consequential information in medical discharge notes. Detecting meaningful features from …
An ontology-based two-stage approach to medical text classification with feature selection by particle swarm optimisation
Document classification (DC) is the task of assigning pre-defined labels to unseen
documents by utilizing a model trained on the available labeled documents. DC has …
documents by utilizing a model trained on the available labeled documents. DC has …
Ontology-guided data augmentation for medical document classification
Extracting meaningful features from unstructured text is one of the most challenging tasks in
medical document classification. The various domain specific expressions and synonyms in …
medical document classification. The various domain specific expressions and synonyms in …
Comparing NLP systems to extract entities of eligibility criteria in dietary supplements clinical trials using NLP-ADAPT
A Bompelli, G Silverman, R Finzel, J Vasilakes… - … Conference on Artificial …, 2020 - Springer
Abstract Natural Language Processing (NLP) techniques have been used extensively to
extract concepts from unstructured clinical trial eligibility criteria. Recruiting patients whose …
extract concepts from unstructured clinical trial eligibility criteria. Recruiting patients whose …
A dictionary-based oversampling approach to clinical document classification on small and imbalanced dataset
Medical document classification is one of the prominent research problems in document
classification domain. As medical discharge notes are collected from real patients, they are …
classification domain. As medical discharge notes are collected from real patients, they are …
Stratifying risk of coronary artery disease using discriminative knowledge-guided medical concept pairings from clinical notes
Document classification (DC) is one of the broadly investigated natural language processing
tasks. Medical document classification can support doctors in making decision and improve …
tasks. Medical document classification can support doctors in making decision and improve …
Improving Medical Document Classification via Feature Engineering
M Abdollahi - 2021 - ir.wgtn.ac.nz
Document classification (DC) is the task of assigning the predefined labels to unseen
documents by utilizing the model trained on the available labeled documents. DC has …
documents by utilizing the model trained on the available labeled documents. DC has …
Grožnje človeku zaradi napredka umetne inteligence
K ČULK - 2021 - repozitorij.uni-lj.si
Umetna inteligenca se od svojega akademskega začetka leta 1956 [35] raz-vija v obliko, ki
jo je težko predvideti. Čeprav je od takrat beleženih nekaj vzponov ter padcev tehnologije …
jo je težko predvideti. Čeprav je od takrat beleženih nekaj vzponov ter padcev tehnologije …
An Ontology-based Three-Stage Approach to Medical Text classification with Feature Selection by Particle Swarm Optimisation
The document classification (DC) task assigns predefined classes to unlabeled documents
using trained models. In the medical field, DC is crucial for tasks like categorizing risk factors …
using trained models. In the medical field, DC is crucial for tasks like categorizing risk factors …