Academic Articles & Research Papers

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 ...

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...

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...

User‐Based Evaluation of Explainability Techniques for Misogyny Detection in Code‐Mixed Hindi–English

ABSTRACT Although artificial intelligence (AI) models have demonstrated great success and efficiency in automatically countering online hate speech and misogyny, they suffer from a lack of explainability and transparency. Explainable artifi...

A recurrent neural network framework for flexible and adaptive decision making based on sequence learning.

The brain makes flexible and adaptive responses in a complicated and ever-changing environment for an organism's survival. To achieve this, the brain needs to understand the contingencies between its sensory inputs, actions, and rewards. Th...

Predicting PANSS symptoms in schizophrenia spectrum disorders using speech only: an international, multi-centre, computational secondary analysis across multiple languages.

Assessing perception and equity of cultural ecosystem services in urban parks using social media data

Abstract Scientific assessment of cultural ecosystem services (CESs) levels in urban parks and refined analysis of their spatial equity are essential for residents’ social well-being. However, traditional assessment methods often fail to ca...

Machine Unlearning: A Perspective, Taxonomy, and Benchmark Evaluation

Machine Learning (ML) models trained on large-scale datasets learn useful predictive patterns, but they may also memorize undesired information, leading to risks such as information leakage, bias, copyright violations, and privacy attacks. ...

Developing Clinical Risk Prediction Models for Worsening Heart Failure Events and Death by Left Ventricular Ejection Fraction

Background There is a need to develop electronic health record–based predictive models for worsening heart failure (WHF) events across clinical settings and across the spectrum of left ventricular ejection fraction (LVEF). Methods and Resul...

Commercial applications of natural language processing

Vast quantities of text are becoming available in electronic form, ranging from published documents (e.g., electronic dictionaries, encyclopedias, libraries and archives for information retrieval services), to private databases (e.g., marke...

Survey of Natural Language Processing Techniques in Bioinformatics

Informatics methods, such as text mining and natural language processing, are always involved in bioinformatics research. In this study, we discuss text mining and natural language processing methods in bioinformatics from two perspectives....

Training‐Efficient Personalised Knee Joint Moment Estimation via an Incremental Broad Learning System

ABSTRACT Knee joint moment estimation is a critical component in biomechanical analysis, with profound implications for rehabilitation assessment and the development of assistive devices like exoskeletons. However, existing data‐driven appr...

Lexical Functions in Lexicography and Natural Language Processing

Lexical Functions in Lexicography and Natural Language Processing is entirely devoted to the topic of Lexical Functions, which have been introduced in the framework of the Meaning-Text Theory (MTT) as a means for describing restricted lexic...

Large Language Models and the Elliott Wave Principle: A Multi-Agent Deep Learning Approach to Big Data Analysis in Financial Markets

Traditional technical analysis methods face limitations in accurately predicting trends in today’s complex financial markets. Meanwhile, existing AI-driven approaches, while powerful in processing large datasets, often lack interpretability...

Research on application of GPS-based wireless communication system in highway landslide

Abstract Machine learning is a branch of the field of artificial intelligence. Deep learning is a complex machine learning algorithm that has unique advantages in image recognition, speech recognition, natural language processing, and indus...

Text Filtering through Multi-Pattern Matching: A Case Study of Wu–Manber–Uy on the Language of Uyghur

Given its generality in applications and its high time-efficiency on big data-sets, in recent years, the technique of text filtering through pattern matching has been attracting increasing attention from the field of information retrieval a...

Natural language processing for information assurance and security

This research paper explores a promising interface between natural language processing (NLP) and information assurance and security (IAS). More specificall~ it is devoted to possible applications to, and further dedicated development of, th...

Natural Language Processing of Clinical Notes on Chronic Diseases: Systematic Review

BACKGROUND: Novel approaches that complement and go beyond evidence-based medicine are required in the domain of chronic diseases, given the growing incidence of such conditions on the worldwide population. A promising avenue is the seconda...

On the Explainability of Natural Language Processing Deep Models

Despite their success, deep networks are used as black-box models with outputs that are not easily explainable during the learning and the prediction phases. This lack of interpretability is significantly limiting the adoption of such model...

Leveraging sentiment analysis of food delivery services reviews using deep learning and word embedding

Companies that deliver food (food delivery services, or FDS) try to use customer feedback to identify aspects where the customer experience could be improved. Consumer feedback on purchasing and receiving goods via online platforms is a cru...