AIMC Topic: Natural Language Processing

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Development of a natural language processing algorithm to extract seizure types and frequencies from the electronic health record.

Seizure
OBJECTIVE: To develop a natural language processing (NLP) algorithm to abstract seizure types and frequencies from electronic health records (EHR).

Design of Human Resource Management System Based on Deep Learning.

Computational intelligence and neuroscience
With the advent of the Internet era, the frequency and proportion of candidates obtaining recruitment information through the Internet is getting higher and higher, and the amount of human resources information such as talent information and postinfo...

Adaptive Dense Ensemble Model for Text Classification.

IEEE transactions on cybernetics
Text classification has been widely explored in natural language processing. In this article, we propose a novel adaptive dense ensemble model (AdaDEM) for text classification, which includes local ensemble stage (LES) and global dense ensemble stage...

Riemannian Adaptive Optimization Algorithm and its Application to Natural Language Processing.

IEEE transactions on cybernetics
This article proposes a Riemannian adaptive optimization algorithm to optimize the parameters of deep neural networks. The algorithm is an extension of both AMSGrad in Euclidean space and RAMSGrad on a Riemannian manifold. The algorithm helps to reso...

Validation of a natural language processing algorithm to identify adenomas and measure adenoma detection rates across a health system: a population-level study.

Gastrointestinal endoscopy
BACKGROUND AND AIMS: Measuring adenoma detection rates (ADRs) at the population level is challenging because pathology reports are often reported in an unstructured format; further, there is significant variation in reporting methods across instituti...

Identification of Preanesthetic History Elements by a Natural Language Processing Engine.

Anesthesia and analgesia
BACKGROUND: Methods that can automate, support, and streamline the preanesthesia evaluation process may improve resource utilization and efficiency. Natural language processing (NLP) involves the extraction of relevant information from unstructured t...

Analyzing patient experiences using natural language processing: development and validation of the artificial intelligence patient reported experience measure (AI-PREM).

BMC medical informatics and decision making
BACKGROUND: Evaluating patients' experiences is essential when incorporating the patients' perspective in improving healthcare. Experiences are mainly collected using closed-ended questions, although the value of open-ended questions is widely recogn...

Medical Text Prediction and Suggestion Using Generative Pretrained Transformer Models with Dental Medical Notes.

Methods of information in medicine
BACKGROUND: Generative pretrained transformer (GPT) models are one of the latest large pretrained natural language processing models that enables model training with limited datasets and reduces dependency on large datasets, which are scarce and cost...

BERT-Promoter: An improved sequence-based predictor of DNA promoter using BERT pre-trained model and SHAP feature selection.

Computational biology and chemistry
A promoter is a sequence of DNA that initializes the process of transcription and regulates whenever and wherever genes are expressed in the organism. Because of its importance in molecular biology, identifying DNA promoters are challenging to provid...

An Improved Math Word Problem (MWP) Model Using Unified Pretrained Language Model (UniLM) for Pretraining.

Computational intelligence and neuroscience
Natural Language Understanding (NLU) and Natural Language Generation (NLG) are the general methods that support machine understanding of text content. They play a very important role in the text information processing system including recommendation ...