Academic Articles & Research Papers

Toward a Fit-for-purpose Policy Architecture on Long-term Care in Sub-Saharan Africa: Impasse and a Research Agenda to Overcome it

Context: Perspectives from sub-Saharan Africa (SSA) have featured little in the expanding global debate on long-term care (LTC) policy thus far – despite SSA countries’ embrace of global commitments on the development of equitable and susta...

A Fully Adapted Headstage With Custom Electrode Arrays Designed for Electrophysiological Experiments

Electrophysiological recordings lead amongst the techniques that aim to investigate the dynamics of neural activity sampled from large neural ensembles. However, the financial costs associated with the state-of-the-art technology used to ma...

Understanding patient perspectives on digital therapeutics and its platform for insomnia: insights from focused group interviews

Abstract Background Digital therapeutics (DTx) is a treatment option that uses computer software to provide evidence-based interventions for medical disorders. DTx platforms are digital services that facilitate interactions among stakeholde...

Applied Natural Language Processing

Today, with digitally stored information available in abundance, even for many less commonly spoken languages, this information must by some means be filtered and extracted in order to avoid drowning in it. Automatic summarization is one su...

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. ...

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...

Data augmentation techniques in natural language processing

Data Augmentation (DA) methods – a family of techniques designed for synthetic generation of training data – have shown remarkable results in various Deep Learning and Machine Learning tasks. Despite its widespread and successful adoption w...

Natural language processing in Alzheimer's disease research: Systematic review of methods, data, and efficacy

Abstract INTRODUCTION Alzheimer's disease (AD) prevalence is increasing, with no current cure. Natural language processing (NLP) offers the potential for non‐invasive diagnostics, social burden assessment, and research advancements in AD. M...

A Systematic Review of Natural Language Processing in Healthcare

The healthcare system is a knowledge driven industry which consists of vast and growing volumes of narrative information obtained from discharge summaries/reports, physicians case notes, pathologists as well as radiologists reports.This inf...

Natural Language Processing in Surgery

OBJECTIVE: The aim of this study was to systematically assess the application and potential benefits of natural language processing (NLP) in surgical outcomes research. SUMMARY BACKGROUND DATA: Widespread implementation of electronic health...

Natural language processing and its future in medicine

If accurate clinical information were available electronically, automated applications could be developed to use this information to improve patient care and lower costs. However, to be fully retrievable, clinical information must be struct...

A Model-Driven Approach Employing DSL and Generation Templates to Accelerate the Development of Conversational Agents for Smart Tourism

Conversational agents are intelligent, ubiquitous software applications widely used across various sectors, such as commerce, tourism, and more. Their key benefits include automating tasks, improving customer service, and ensuring service a...

Neural transfer learning for natural language processing

The current generation of neural network-based natural language processing models excels at learning from large amounts of labelled data. Given these capabilities, natural language processing is increasingly applied to new tasks, new domain...

Deep learning for natural language processing: advantages and challenges

Deep learning refers to machine learning technologies for learning and utilizing ‘deep’ artificial neural networks, such as deep neural networks (DNN), convolutional neural networks (CNN) and recurrent neural networks (RNN). Recently, deep ...

Specialized Large Language Model for Standardization of Locomotive Maintenance Data

Standardization is one of the key steps to analyze locomotive overhaul data with a focus on reliability-centered maintenance (RCM). However, traditional manual methods encounter challenges such as small sample sizes, non-standardized data f...

Natural Language Processing in Oncology

IMPORTANCE: Natural language processing (NLP) has the potential to accelerate translation of cancer treatments from the laboratory to the clinic and will be a powerful tool in the era of personalized medicine. This technology can harvest im...

Link Predictions with Bi-Level Routing Attention

Background/Objectives: Knowledge Graphs (KGs) are often incomplete, which can significantly impact the performance of downstream applications. Manual completion of KGs is time-consuming and costly, emphasizing the importance of developing a...

Costs, compensations, and community building of implicit prosocial behavior in college dormitory environments: a mixed-methods study.

Studying the causes of humidity fluctuations in food products within industrial environments

The production of processed foods and animal nutrition requires precise control over product characteristics to ensure consistent quality. Unexpected fluctuations in key parameters, particularly humidity, can lead to significant financial l...

Computer Vision System for Automatic Counting of Planting Microsites Using UAV Imagery

Mechanical site preparation by mounding is often used by the forest industry to provide optimal growth conditions for tree seedlings. Prior to planting, an essential step consists in estimating the number of mounds at each planting block, w...