AIMC Topic: Natural Language Processing

Clear Filters Showing 1481 to 1490 of 3983 articles

Ambiguous and Incomplete: Natural Language Processing Reveals Problematic Reporting Styles in Thyroid Ultrasound Reports.

Methods of information in medicine
OBJECTIVE: Natural language processing (NLP) systems convert unstructured text into analyzable data. Here, we describe the performance measures of NLP to capture granular details on nodules from thyroid ultrasound (US) reports and reveal critical iss...

Attention based automated radiology report generation using CNN and LSTM.

PloS one
The automated generation of radiology reports provides X-rays and has tremendous potential to enhance the clinical diagnosis of diseases in patients. A new research direction is gaining increasing attention that involves the use of hybrid approaches ...

CODER: Knowledge-infused cross-lingual medical term embedding for term normalization.

Journal of biomedical informatics
OBJECTIVE: This paper aims to propose knowledge-aware embedding, a critical tool for medical term normalization.

Derivation of a natural language processing algorithm to identify febrile infants.

Journal of hospital medicine
BACKGROUND: Diagnostic codes can retrospectively identify samples of febrile infants, but sensitivity is low, resulting in many febrile infants eluding detection. To ensure study samples are representative, an improved approach is needed.

Machine Translation System Using Deep Learning for English to Urdu.

Computational intelligence and neuroscience
Machine translation is an ongoing field of research from the last decades. The main aim of machine translation is to remove the language barrier. Earlier research in this field started with the direct word-to-word replacement of source language by th...

AMMU: A survey of transformer-based biomedical pretrained language models.

Journal of biomedical informatics
Transformer-based pretrained language models (PLMs) have started a new era in modern natural language processing (NLP). These models combine the power of transformers, transfer learning, and self-supervised learning (SSL). Following the success of th...

Machine learning and natural language processing to identify falls in electronic patient care records from ambulance attendances.

Informatics for health & social care
We derived machine learning models utilizing features generated by natural language processing (NLP) of free-text data from an ambulance services provider to identify fall cases. The data comprised samples of electronic patient care records care reco...

Document-level medical relation extraction via edge-oriented graph neural network based on document structure and external knowledge.

BMC medical informatics and decision making
OBJECTIVE: Relation extraction (RE) is a fundamental task of natural language processing, which always draws plenty of attention from researchers, especially RE at the document-level. We aim to explore an effective novel method for document-level med...

A Data-Driven Iterative Approach for Semi-automatically Assessing the Correctness of Medication Value Sets: A Proof of Concept Based on Opioids.

Methods of information in medicine
BACKGROUND: Value sets are lists of terms (e.g., opioid medication names) and their corresponding codes from standard clinical vocabularies (e.g., RxNorm) created with the intent of supporting health information exchange and research. Value sets are ...

The Use of Artificial Intelligence and Machine Learning in Surgery: A Comprehensive Literature Review.

The American surgeon
Interest in the use of artificial intelligence (AI) and machine learning (ML) in medicine has grown exponentially over the last few years. With its ability to enhance speed, precision, and efficiency, AI has immense potential, especially in the field...