AIMC Topic: Natural Language Processing

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A Parser to Support the Definition of Access Control Policies and Rules Using Natural Languages.

Journal of medical systems
As a consequence of the epidemiological transition towards non-communicable diseases, integrated care approaches are required, not solely focused on medical purposes, but also on a range of essential activities for the maintenance of the individuals'...

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 ...

Recent advances in Swedish and Spanish medical entity recognition in clinical texts using deep neural approaches.

BMC medical informatics and decision making
BACKGROUND: Text mining and natural language processing of clinical text, such as notes from electronic health records, requires specific consideration of the specialized characteristics of these texts. Deep learning methods could potentially mitigat...

Natural language processing to facilitate breast cancer research and management.

The breast journal
The medical literature has been growing exponentially, and its size has become a barrier for physicians to locate and extract clinically useful information. As a promising solution, natural language processing (NLP), especially machine learning (ML)-...

Modeling aspects of the language of life through transfer-learning protein sequences.

BMC bioinformatics
BACKGROUND: Predicting protein function and structure from sequence is one important challenge for computational biology. For 26 years, most state-of-the-art approaches combined machine learning and evolutionary information. However, for some applica...

Terminologies augmented recurrent neural network model for clinical named entity recognition.

Journal of biomedical informatics
OBJECTIVE: We aimed to enhance the performance of a supervised model for clinical named-entity recognition (NER) using medical terminologies. In order to evaluate our system in French, we built a corpus for 5 types of clinical entities.

Task definition, annotated dataset, and supervised natural language processing models for symptom extraction from unstructured clinical notes.

Journal of biomedical informatics
INTRODUCTION: Machine learning (ML) and natural language processing have great potential to improve information extraction (IE) within electronic medical records (EMRs) for a wide variety of clinical search and summarization tools. Despite ML advance...

Medication-rights detection using incident reports: A natural language processing and deep neural network approach.

Health informatics journal
Medication errors often occurred due to the breach of medication rights that are the right patient, the right drug, the right time, the right dose and the right route. The aim of this study was to develop a medication-rights detection system using na...

Boosting ICD multi-label classification of health records with contextual embeddings and label-granularity.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: This work deals with clinical text mining, a field of Natural Language Processing applied to biomedical informatics. The aim is to classify Electronic Health Records with respect to the International Classification of Diseas...

Story Arcs in Serious Illness: Natural Language Processing features of Palliative Care Conversations.

Patient education and counseling
OBJECTIVE: Serious illness conversations are complex clinical narratives that remain poorly understood. Natural Language Processing (NLP) offers new approaches for identifying hidden patterns within the lexicon of stories that may reveal insights abo...