AIMC Topic: Natural Language Processing

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Harnessing NLP to investigate biomarker interactions and CVD risks in elderly chronic kidney disease patients.

SLAS technology Jan 9, 2025
Chronic kidney disease (CKD) significantly increases the risk of CVD diseases, particularly among elderly patients. Understanding the interaction between several biomarkers and cardiovascular (CVD) risks is crucial for improving patient outcomes and ...
Cardiovascular Diseases Renal Insufficiency, Chronic Humans Natural Language Processing Fibroblast Growth Factor-23 Biomarkers Aged Aged, 80 and over Female Male Risk Factors
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Leveraging Natural Language Processing and Machine Learning Methods for Adverse Drug Event Detection in Electronic Health/Medical Records: A Scoping Review.

Drug safety Jan 9, 2025
BACKGROUND: Natural language processing (NLP) and machine learning (ML) techniques may help harness unstructured free-text electronic health record (EHR) data to detect adverse drug events (ADEs) and thus improve pharmacovigilance. However, evidence ...
Humans Machine Learning Electronic Health Records Adverse Drug Reaction Reporting Systems Natural Language Processing Drug-Related Side Effects and Adverse Reactions Pharmacovigilance
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Early Identification of Language Disorders Using Natural Language Processing and Machine Learning: Challenges and Emerging Approaches.

Journal of speech, language, and hearing research : JSLHR Jan 9, 2025
PURPOSE: Recent advances in artificial intelligence provide opportunities to capture and represent complex features of human language in a more automated manner, offering potential means of improving the efficiency of language assessment. This review...
Language Development Disorders Humans Early Diagnosis Child Machine Learning Language Tests Natural Language Processing Language Disorders
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Prompt Tuning of Deep Neural Networks for Speaker-Adaptive Visual Speech Recognition.

IEEE transactions on pattern analysis and machine intelligence Jan 9, 2025
Visual Speech Recognition (VSR) aims to infer speech into text depending on lip movements alone. As it focuses on visual information to model the speech, its performance is inherently sensitive to personal lip appearances and movements, and this make...
Humans Neural Networks, Computer Image Processing, Computer-Assisted Natural Language Processing Speech Recognition Software Algorithms Deep Learning Speech
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Applying Natural Language Processing Techniques to Map Trends in Insomnia Treatment Terms on the r/Insomnia Subreddit: Infodemiology Study.

Journal of medical Internet research Jan 9, 2025
BACKGROUND: People share health-related experiences and treatments, such as for insomnia, in digital communities. Natural language processing tools can be leveraged to understand the terms used in digital spaces to discuss insomnia and insomnia treat...
Natural Language Processing Sleep Initiation and Maintenance Disorders Humans
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Widespread use of ChatGPT and other Artificial Intelligence tools among medical students in Uganda: A cross-sectional study.

PloS one Jan 9, 2025
BACKGROUND: Chat Generative Pre-trained Transformer (ChatGPT) is a 175-billion-parameter natural language processing model that uses deep learning algorithms trained on vast amounts of data to generate human-like texts such as essays. Consequently, i...
Adolescent Uganda Universities Natural Language Processing Male Deep Learning Surveys and Questionnaires Students, Medical Cross-Sectional Studies Humans Artificial Intelligence Female Young Adult Adult
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Quantum mixed-state self-attention network.

Neural networks : the official journal of the International Neural Network Society Jan 8, 2025
Attention mechanisms have revolutionized natural language processing. Combining them with quantum computing aims to further advance this technology. This paper introduces a novel Quantum Mixed-State Self-Attention Network (QMSAN) for natural language...
Attention Algorithms Humans Natural Language Processing Neural Networks, Computer Quantum Theory
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Comparison of active learning algorithms in classifying head computed tomography reports using bidirectional encoder representations from transformers.

International journal of computer assisted radiology and surgery Jan 8, 2025
PURPOSE: Systems equipped with natural language (NLP) processing can reduce missed radiological findings by physicians, but the annotation costs are burden in the development. This study aimed to compare the effects of active learning (AL) algorithms...
Problem-Based Learning Humans Head Algorithms Radiology Information Systems Tomography, X-Ray Computed Natural Language Processing Supervised Machine Learning
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Assessment of Real-Time Natural Language Processing for Improving Diagnostic Specificity: A Prospective, Crossover Exploratory Study.

Applied clinical informatics Jan 8, 2025
BACKGROUND:  Reliable, precise, timely, and clear documentation of diagnoses is difficult. Poor specificity or the absence of diagnostic documentation can lead to decreased revenue and increased payor denials, audits, and queries to providers. Nuance...
Humans Prospective Studies Diagnosis Natural Language Processing Electronic Health Records Cross-Over Studies Sensitivity and Specificity Documentation
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Utilizing natural language processing to identify pediatric patients experiencing status epilepticus.

Seizure Jan 8, 2025
PURPOSE: Compare the identification of patients with established status epilepticus (ESE) and refractory status epilepticus (RSE) in electronic health records (EHR) using human review versus natural language processing (NLP) assisted review.
Infant Adolescent Child, Preschool Humans Status Epilepticus Child Young Adult Machine Learning Male Electronic Health Records Support Vector Machine Female Natural Language Processing
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