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Found 12 papers, 0 papers with code
Automatic Transformation of Clinical Narratives into Structured Format
For the “Diagnosis” section a deep learning text-based encoding into ICD-10 codes is applied using MBG-ClinicalBERT - a fine-tuned ClinicalBERT model for Bulgarian medical text.
Comparative Analysis of Fine-tuned Deep Learning Language Models for ICD-10 Classification Task for Bulgarian Language
In our research study all BERT models are fine-tuned with additional medical texts in Bulgarian and then applied to the classification task for encoding medical diagnoses in Bulgarian into ICD-10 codes.
Application of Deep Learning Methods to SNOMED CT Encoding of Clinical Texts: From Data Collection to Extreme Multi-Label Text-Based Classification
We attempt to solve this problem through automatic SNOMED CT encoding, where SNOMED CT is one of the most widely used and comprehensive clinical term ontologies.
Deep learning contextual models for prediction of sport event outcome from sportsman's interviews
We test the hypothesis that the sports results can be predicted by using natural language processing and machine learning techniques applied over interviews with the players shortly before the sport events.
Risk Factors Extraction from Clinical Texts based on Linked Open Data
The idea is to determine whether a patient has risk factors for a specific disease analyzing only his/her outpatient records.
Comparison of Machine Learning Approaches for Industry Classification Based on Textual Descriptions of Companies
This paper addresses the task of categorizing companies within industry classification schemes.
Mining Association Rules from Clinical Narratives
Unfortunately, most frequent pattern mining approaches do not use contextual information for extracted patterns: general patterns are extracted regardless of the context.
Towards Lexical Chains for Knowledge-Graph-based Word Embeddings
Word vectors with varying dimensionalities and produced by different algorithms have been extensively used in NLP.
Identification of Risk Factors in Clinical Texts through Association Rules
We describe a method which extracts Association Rules from texts in order to recognise verbalisations of risk factors.
Annotation of Clinical Narratives in Bulgarian language
In this paper we describe annotation process of clinical texts with morphosyntactic and semantic information.
