AIMC Topic: Natural Language Processing

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Clinical Text Data Categorization and Feature Extraction Using Medical-Fissure Algorithm and Neg-Seq Algorithm.

Computational intelligence and neuroscience
A large amount of patient information has been gathered in Electronic Health Records (EHRs) concerning their conditions. An EHR, as an unstructured text document, serves to maintain health by identifying, treating, and curing illnesses. In this resea...

Effective Transfer Learning with Label-Based Discriminative Feature Learning.

Sensors (Basel, Switzerland)
The performance of natural language processing with a transfer learning methodology has improved by applying pre-training language models to downstream tasks with a large number of general data. However, because the data used in pre-training are irre...

Intelligent virtual case learning system based on real medical records and natural language processing.

BMC medical informatics and decision making
BACKGROUND: Modernizing medical education by using artificial intelligence and other new technologies to improve the clinical thinking ability of medical students is an important research topic in recent years. Prominent medical universities are acti...

An empirical evaluation of Lex/Yacc and ANTLR parser generation tools.

PloS one
Parsers are used in different software development scenarios such as compiler construction, data format processing, machine-level translation, and natural language processing. Due to the widespread usage of parsers, there exist different tools aimed ...

FlauBERT vs. CamemBERT: Understanding patient's answers by a French medical chatbot.

Artificial intelligence in medicine
In a number of circumstances, obtaining health-related information from a patient is time-consuming, whereas a chatbot interacting efficiently with that patient might help saving health care professional time and better assisting the patient. Making ...

Capturing Surgical Data: Comparing a Quality Improvement Registry to Natural Language Processing and Manual Chart Review.

Journal of gastrointestinal surgery : official journal of the Society for Surgery of the Alimentary Tract
INTRODUCTION: Collecting accurate operative details remains a limitation of surgical research. Surgeon-entered data in clinical registries offers one solution, but natural language processing (NLP) has emerged as a modality for automating manual char...

Dynamic Embedding Projection-Gated Convolutional Neural Networks for Text Classification.

IEEE transactions on neural networks and learning systems
Text classification is a fundamental and important area of natural language processing for assigning a text into at least one predefined tag or category according to its content. Most of the advanced systems are either too simple to get high accuracy...

Connecting Text Classification with Image Classification: A New Preprocessing Method for Implicit Sentiment Text Classification.

Sensors (Basel, Switzerland)
As a research hotspot in the field of natural language processing (NLP), sentiment analysis can be roughly divided into explicit sentiment analysis and implicit sentiment analysis. However, due to the lack of obvious emotion words in the implicit sen...

Prediction of clinical trial enrollment rates.

PloS one
Clinical trials represent a critical milestone of translational and clinical sciences. However, poor recruitment to clinical trials has been a long standing problem affecting institutions all over the world. One way to reduce the cost incurred by ins...

Deep Learning-based detection of psychiatric attributes from German mental health records.

International journal of medical informatics
BACKGROUND: Health care records provide large amounts of data with real-world and longitudinal aspects, which is advantageous for predictive analyses and improvements in personalized medicine. Text-based records are a main source of information in me...