Academic Articles & Research Papers

Natural Language Processing and Semantical Representation of Medical Texts

For medical records, the challenge for the present decade is Natural Language Processing (NLP) of texts, and the construction of an adequate Knowledge Representation. This article describes the components of an NLP system, which is currentl...

A bibliometric analysis of natural language processing in medical research

BACKGROUND: Natural language processing (NLP) has become an increasingly significant role in advancing medicine. Rich research achievements of NLP methods and applications for medical information processing are available. It is of great sig...

Natural language processing in an operational clinical information system

Abstract This paper describes a natural language text extraction system, called MEDLEE, that has been applied to the medical domain. The system extracts, structures, and encodes clinical information from textual patient reports. It was inte...

The ethical PROMISE NFR dataset: data for ethical concern classification in software requirements.

Enhancing sentiment classification on small datasets through data augmentation and transfer learning

Abstract Small-scale sentiment classification often suffers from data scarcity, which limits the generalization ability of the models. This study evaluates and compares the effectiveness of three data augmentation strategies: Easy Data Augm...

A Multi-Stage NLP Framework for Knowledge Discovery from Crop Disease Research Literature

Extracting and organizing knowledge from the agricultural crop disease research literature are challenging tasks because of the heterogeneous terminologies, complicated symptom descriptions, and unstructured nature of scientific documents. ...

D‐BERT: Incorporating dependency‐based attention into BERT for relation extraction

Abstract Relation extraction between entity pairs is an increasingly critical area in natural language processing. Recently, the pre‐trained bidirectional encoder representation from transformer (BERT) performs excellently on the text class...

Sequence Decision Transformer for Adaptive Traffic Signal Control

Urban traffic congestion poses significant economic and environmental challenges worldwide. To mitigate these issues, Adaptive Traffic Signal Control (ATSC) has emerged as a promising solution. Recent advancements in deep reinforcement lear...

Quantifying Gender Bias in Large Language Models Using Information-Theoretic and Statistical Analysis

Large language models (LLMs) have revolutionized natural language processing across diverse domains, yet they also raise critical fairness and ethical concerns, particularly regarding gender bias. In this study, we conduct a systematic, mat...

Natural Language Processing Techniques for Text Classification of Biomedical Documents: A Systematic Review

The classification of biomedical literature is engaged in a number of critical issues that physicians are expected to answer. In many cases, these issues are extremely difficult. This can be conducted for jobs such as diagnosis and treatmen...

Unlocking Clinical Data from Narrative Reports: A Study of Natural Language Processing

OBJECTIVE: To evaluate the automated detection of clinical conditions described in narrative reports. DESIGN: Automated methods and human experts detected the presence or absence of six clinical conditions in 200 admission chest radiograph ...

Advancements in natural language processing: Implications, challenges, and future directions

This research delves into the latest advancements in Natural Language Processing (NLP) and their broader implications, challenges, and future directions. With the ever-increasing volume of text data generated daily from diverse sources, ext...

Application of Convolutional Neural Network in Natural Language Processing

Convolutional neural network (Convolutionl Neural Network, CNN) is a multiple-layer neural network method to learn hierarchical characteristic of data. In recent years, CNN has developed rapidly in the design and calculation of natural lang...

Natural Language Processing Technologies in Radiology Research and Clinical Applications

The migration of imaging reports to electronic medical record systems holds great potential in terms of advancing radiology research and practice by leveraging the large volume of data continuously being updated, integrated, and shared. How...

Applications of natural language processing and large language models in materials discovery

The transformative impact of artificial intelligence (AI) technologies on materials science has revolutionized the study of materials problems. By leveraging well-characterized datasets derived from the scientific literature, AI-powered too...

Python Natural Language Processing

Leverage the power of machine learning and deep learning to extract information from text dataAbout This BookImplement Machine Learning and Deep Learning techniques for efficient natural language processingGet started with NLTK and implemen...

BioBBC: a multi-feature model that enhances the detection of biomedical entities

Abstract The rapid increase in biomedical publications necessitates efficient systems to automatically handle Biomedical Named Entity Recognition (BioNER) tasks in unstructured text. However, accurately detecting biomedical entities is quit...

Neither Telling nor Describing. Reflective Passages and Perceived Reflectiveness 1700–1945

The paper analyses within-fiction reflections in 250 years of literary history. To this end, we formalised the concept of “reflective passage”, demonstrate how our annotation categories are deduced from literary theory and derive three subp...

Construction of a knowledge graph for the educational statistical indicator system based on large language models

Current statistical work in the field of educational development faces challenges such as low knowledge-retrieval efficiency and high technical barriers to data utilization. This study focuses on the knowledge related to the indicator syste...

A systematic review of natural language processing applied to radiology reports

BACKGROUND: Natural language processing (NLP) has a significant role in advancing healthcare and has been found to be key in extracting structured information from radiology reports. Understanding recent developments in NLP application to r...