AIMC Topic: Natural Language Processing

Clear Filters Showing 1071 to 1080 of 3983 articles

Automated tabulation of clinical trial results: A joint entity and relation extraction approach with transformer-based language representations.

Artificial intelligence in medicine
Evidence-based medicine, the practice in which healthcare professionals refer to the best available evidence when making decisions, forms the foundation of modern healthcare. However, it relies on labour-intensive systematic reviews, where domain spe...

Social Listening for Product Design Requirement Analysis and Segmentation: A Graph Analysis Approach with User Comments Mining.

Big data
This study investigates customers' product design requirements through online comments from social media, and quickly translates these needs into product design specifications. First, the exponential discriminative snowball sampling method was propos...

Natural language processing deep learning models for the differential between high-grade gliomas and metastasis: what if the key is how we report them?

European radiology
OBJECTIVES: The differential between high-grade glioma (HGG) and metastasis remains challenging in common radiological practice. We compare different natural language processing (NLP)-based deep learning models to assist radiologists based on data co...

On exploring node-feature and graph-structure diversities for node drop graph pooling.

Neural networks : the official journal of the International Neural Network Society
Graph Neural Networks (GNNs) have been successfully applied to graph-level tasks in various fields such as biology, social networks, computer vision, and natural language processing. For the graph-level representations learning of GNNs, graph pooling...

Application of specialized word embeddings and named entity and attribute recognition to the problem of unsupervised automated clinical coding.

Computers in biology and medicine
Notes documented by clinicians, such as patient histories, hospital courses, lab reports and others are often annotated with standardized clinical codes by medical coders to facilitate a variety of secondary processing applications such as billing an...

Machine translation of standardised medical terminology using natural language processing: A scoping review.

New biotechnology
Standardised medical terminologies are used to ensure accurate and consistent communication of information and to facilitate data exchange. Currently, many terminologies are only available in English, which hinders international research and automate...

A scoping review on multimodal deep learning in biomedical images and texts.

Journal of biomedical informatics
OBJECTIVE: Computer-assisted diagnostic and prognostic systems of the future should be capable of simultaneously processing multimodal data. Multimodal deep learning (MDL), which involves the integration of multiple sources of data, such as images an...

Annotated dataset creation through large language models for non-english medical NLP.

Journal of biomedical informatics
Obtaining text datasets with semantic annotations is an effortful process, yet crucial for supervised training in natural language processing (NLP). In general, developing and applying new NLP pipelines in domain-specific contexts for tasks often req...

Application of Natural Language Processing in Total Joint Arthroplasty: Opportunities and Challenges.

The Journal of arthroplasty
Total joint arthroplasty is becoming one of the most common surgeries within the United States, creating an abundance of analyzable data to improve patient experience and outcomes. Unfortunately, a large majority of this data is concealed in electron...

Improving chest X-ray report generation by leveraging warm starting.

Artificial intelligence in medicine
Automatically generating a report from a patient's Chest X-rays (CXRs) is a promising solution to reducing clinical workload and improving patient care. However, current CXR report generators-which are predominantly encoder-to-decoder models-lack the...