AIMC Topic: Narration
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Transformer-based Model Captures Neural Representation Differences between Nouns and Verbs in Spoken Narratives.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2024
Nouns and verbs constitute the fundamental elements of human language systems. Abundant studies have demonstrated that nouns and verbs exhibit different representations in both biological brains and various advanced deep neural networks (DNNs). Here,...
Using natural language processing to link patients' narratives to visual capabilities and sentiments.
Optometry and vision science : official publication of the American Academy of Optometry
Jun 1, 2024
SIGNIFICANCE: Analyzing narratives in patients' medical records using a framework that combines natural language processing (NLP) and machine learning may help uncover the underlying patterns of patients' visual capabilities and challenges that they ...
Multimodal learning for temporal relation extraction in clinical texts.
Journal of the American Medical Informatics Association : JAMIA
May 20, 2024
OBJECTIVES: This study focuses on refining temporal relation extraction within medical documents by introducing an innovative bimodal architecture. The overarching goal is to enhance our understanding of narrative processes in the medical domain, par...
Narrative Feature or Structured Feature? A Study of Large Language Models to Identify Cancer Patients at Risk of Heart Failure.
AMIA ... Annual Symposium proceedings. AMIA Symposium
Jan 1, 2024
Cancer treatments are known to introduce cardiotoxicity, negatively impacting outcomes and survivorship. Identifying cancer patients at risk of heart failure (HF) is critical to improving cancer treatment outcomes and safety. This study examined mach...
Extraction of Normalized Symptom Mentions From Clinical Narratives Using Large Language Models.
AMIA ... Annual Symposium proceedings. AMIA Symposium
Jan 1, 2024
Symptoms, or subjective experiences of patients which can indicate underlying pathology, are important for guiding clinician decision-making and revealing patient wellbeing. However, they are difficult to study because information is primarily found ...
Natural Language Processing in Surgery: A Systematic Review and Meta-analysis.
Annals of surgery
May 1, 2021
OBJECTIVE: The aim of this study was to systematically assess the application and potential benefits of natural language processing (NLP) in surgical outcomes research.
Artificial Intelligence for Personalized Preventive Adolescent Healthcare.
The Journal of adolescent health : official publication of the Society for Adolescent Medicine
Aug 1, 2020
Recent advances in artificial intelligence (AI) are creating new opportunities for personalizing technology-based health interventions to adolescents. This article provides a computer science perspective on how emerging AI technologies-intelligent le...
Supervised Learning for the ICD-10 Coding of French Clinical Narratives.
Studies in health technology and informatics
Jun 16, 2020
Automatic detection of ICD-10 codes in clinical documents has become a necessity. In this article, after a brief reminder of the existing work, we present a corpus of French clinical narratives annotated with the ICD-10 codes. Then, we propose automa...
Clinical Concept Normalization on Medical Records Using Word Embeddings and Heuristics.
Studies in health technology and informatics
Jun 16, 2020
Electronic health records contain valuable information on patients' clinical history in the form of free text. Manually analyzing millions of these documents is unfeasible and automatic natural language processing methods are essential for efficientl...
Advancing the state of the art in automatic extraction of adverse drug events from narratives.
Journal of the American Medical Informatics Association : JAMIA
Jan 1, 2020
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