Academic Articles & Research Papers

Artificial intelligence in clinical medicine: a state-of-the-art overview of systematic reviews with methodological recommendations for improved reporting

Medicine has become increasingly receptive to the use of artificial intelligence (AI). This overview of systematic reviews (SRs) aims to categorise current evidence about it and identify the current methodological state of the art in the fi...

Self-Repair and Language Selection in Bilingual Speech Processing

In psycholinguistic research the exact level of language selection in bilingual lexical access is still controversial and current models of bilingual speech production offer conflicting statements about the mechanisms and location of langua...

TransKGQA: Enhanced Knowledge Graph Question Answering With Sentence Transformers

Knowledge Graph Question Answering (KGQA) plays a crucial role in extracting valuable insights from interconnected information. Existing methods, while commendable, face challenges such as contextual ambiguity and limited adaptability to di...

Modeling Semantic Relations Expressed by Prepositions

Classifying Characteristics of Opioid Use Disorder From Hospital Discharge Summaries Using Natural Language Processing

BackgroundOpioid use disorder (OUD) is underdiagnosed in health system settings, limiting research on OUD using electronic health records (EHRs). Medical encounter notes can enrich structured EHR data with documented signs and symptoms of O...

Improving the trial efficiency of criminal cases with the assistance of artificial intelligence

Abstract This study explores the application of artificial intelligence (AI) in improving the trial efficiency of criminal cases. Using a dataset consisting of 500 criminal case records, including minor, ordinary, and complex cases, we appl...

Bias and Fairness in Natural Language Processing

Recent advances in data-driven machine learning techniques (e.g., deep neural networks) have revolutionized many natural language processing applications. These approaches automatically learn how to make decisions based on the statistics an...

Natural language processing with transformers: a review

Natural language processing (NLP) tasks can be addressed with several deep learning architectures, and many different approaches have proven to be efficient. This study aims to briefly summarize the use cases for NLP tasks along with the ma...

Performance, Recalibration, and Implementation of In-Hospital Mortality Prediction Models for Myocardial Infarction.

Moral engine model: conceptualizing moral injury as a wound to the self caused by rupturing of defining and sustaining emotional attachments.

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...

Emergency department triaging using ChatGPT based on emergency severity index principles: a cross-sectional study

Abstract Erroneous and delayed triage in an increasingly crowded emergency department (ED). ChatGPT is an artificial intelligence model developed by OpenAI® and is being trained for use in natural language processing tasks. Our study aims t...

A call for an interdisciplinary ethical foundation for GenAI governance in higher education

Abstract Generative artificial intelligence (GenAI) systems are increasingly embedded in higher education, shaping writing, instructional design, and institutional approaches to academic integrity. In response, universities have developed p...

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...

A Simple Introduction to Maximum Entropy Models for Natural Language Processing

Many problems in natural language processing can be viewed as linguistic classification problems, in which linguistic contexts are used to predict linguistic classes. Maximum entropy models offer a clean way to combine diverse pieces of con...

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...

Natural Language Processing in Psychiatry

The potential benefit of artificial intelligence (AI) technology as a tool of psychiatry has not been well defined. In this essay, the technology of natural language processing and its position with regard to the two main schools of AI is c...