AIMC Topic: Natural Language Processing

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Emotional reactions to infertility diagnosis: thematic and natural language processing analyses of the 1000 Dreams survey.

Reproductive biomedicine online
RESEARCH QUESTION: What are the emotional effects of infertility on patients, partners, or both, and how can qualitative thematic analyses and natural language processing (NLP) help evaluate textual data?

Multi-granularity heterogeneous graph attention networks for extractive document summarization.

Neural networks : the official journal of the International Neural Network Society
Extractive document summarization is a fundamental task in natural language processing (NLP). Recently, several Graph Neural Networks (GNNs) are proposed for this task. However, most existing GNN-based models can neither effectively encode semantic n...

Automated extraction of information of lung cancer staging from unstructured reports of PET-CT interpretation: natural language processing with deep-learning.

BMC medical informatics and decision making
BACKGROUND: Extracting metastatic information from previous radiologic-text reports is important, however, laborious annotations have limited the usability of these texts. We developed a deep-learning model for extracting primary lung cancer sites an...

Natural Language Processing in Spine Surgery: A Systematic Review of Applications, Bias, and Reporting Transparency.

World neurosurgery
BACKGROUND: Natural language processing (NLP) is a discipline of machine learning concerned with the analysis of language and text. Although NLP has been applied to various forms of clinical text, the applications and utility of NLP in spine surgery ...

Improvement of intervention information detection for automated clinical literature screening during systematic review.

Journal of biomedical informatics
Systematic literature review (SLR) is a crucial method for clinicians and policymakers to make their decisions in a flood of new clinical studies. Because manual literature screening in SLR is a highly laborious task, its automation by natural langua...

Using natural language processing and machine learning to replace human content coders.

Psychological methods
Content analysis is a common and flexible technique to quantify and make sense of qualitative data in psychological research. However, the practical implementation of content analysis is extremely labor-intensive and subject to human coder errors. Ap...

Natural Language Processing in Radiology: Update on Clinical Applications.

Journal of the American College of Radiology : JACR
Radiological reports are a valuable source of information used to guide clinical care and support research. Organizing and managing this content, however, frequently requires several manual curations because of the more common unstructured nature of ...

Application of Deep Learning in Generating Structured Radiology Reports: A Transformer-Based Technique.

Journal of digital imaging
Since radiology reports needed for clinical practice and research are written and stored in free-text narrations, extraction of relative information for further analysis is difficult. In these circumstances, natural language processing (NLP) techniqu...

Text-Based Emotion Recognition Using Deep Learning Approach.

Computational intelligence and neuroscience
Sentiment analysis is a method to identify people's attitudes, sentiments, and emotions towards a given goal, such as people, activities, organizations, services, subjects, and products. Emotion detection is a subset of sentiment analysis as it predi...

OARD: Open annotations for rare diseases and their phenotypes based on real-world data.

American journal of human genetics
Diagnosis for rare genetic diseases often relies on phenotype-driven methods, which hinge on the accuracy and completeness of the rare disease phenotypes in the underlying annotation knowledgebase. Existing knowledgebases are often manually curated w...