ArticleAMIA ... Annual Symposium proceedings. AMIA Symposium2017
Intelligent Word Embeddings of Free-Text Radiology Reports.
Article in AMIA ... Annual Symposium proceedings. AMIA Symposium, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
22 citing papers in PubMed, 1 synthesis or guideline pooled it, 15 citations in OpenAlex.
- A systematic review of natural language processing applied to radiology reports.BMC medical informatics and decision making · 2021Pooled it
- Artificial Intelligence Across the Radiology Workflow: A Nine-Stage Narrative Review.Diagnostics (Basel, Switzerland) · 2026Review
- TECRR: a benchmark dataset of radiological reports for BI-RADS classification with machine learning, deep learning, and large language model baselines.BMC medical informatics and decision making · 2024Article
- Extraction and Quantification of Words Representing Degrees of Diseases: Combining the Fuzzy C-Means Method and Gaussian Membership.JMIR formative research · 2022Article
- Deep Learning Approaches for Predicting Glaucoma Progression Using Electronic Health Records and Natural Language Processing.Ophthalmology science · 2022Article
- Improving medical term embeddings using UMLS Metathesaurus.BMC medical informatics and decision making · 2022Article
- Development of a Pipeline for Adverse Drug Reaction Identification in Clinical Notes: Word Embedding Models and String Matching.JMIR medical informatics · 2022Article
- Generalized Zero-Shot Chest X-Ray Diagnosis Through Trait-Guided Multi-View Semantic Embedding With Self-Training.IEEE transactions on medical imaging · 2021Article
- Development and web deployment of an automated neuroradiology MRI protocoling tool with natural language processing.BMC medical informatics and decision making · 2021Article
- Comparative analysis of machine learning algorithms for computer-assisted reporting based on fully automated cross-lingual RadLex mappings.Scientific reports · 2021Article
- A Fusion NLP Model for the Inference of Standardized Thyroid Nodule Malignancy Scores from Radiology Report Text.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2021Article
- Domain specific word embeddings for natural language processing in radiology.Journal of biomedical informatics · 2021Article
- Intrinsic Evaluation of Contextual and Non-contextual Word Embeddings using Radiology Reports.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2021Article
- Identifying and Predicting Intentional Self-Harm in Electronic Health Record Clinical Notes: Deep Learning Approach.JMIR medical informatics · 2020Article
- Clinical Text Data in Machine Learning: Systematic Review.JMIR medical informatics · 2020Review
- Automated detection of altered mental status in emergency department clinical notes: a deep learning approach.BMC medical informatics and decision making · 2019Article
- Comparative effectiveness of convolutional neural network (CNN) and recurrent neural network (RNN) architectures for radiology text report classification.Artificial intelligence in medicine · 2019Article
- Automatic inference of BI-RADS final assessment categories from narrative mammography report findings.Journal of biomedical informatics · 2019Article
- DeepSeeNet: A Deep Learning Model for Automated Classification of Patient-based Age-related Macular Degeneration Severity from Color Fundus Photographs.Ophthalmology · 2019Article
- Natural Language Processing for Automated Quantification of Brain Metastases Reported in Free-Text Radiology Reports.JCO clinical cancer informatics · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 1 institution in 1 country.
Funding
Abstract
Radiology reports are a rich resource for advancing deep learning applications in medicine by leveraging the large volume of data continuously being updated, integrated, and shared. However, there are significant challenges as well, largely due to the ambiguity and subtlety of natural language. We propose a hybrid strategy that combines semantic-dictionary mapping and word2vec modeling for creating dense vector embeddings of free-text radiology reports. Our method leverages the benefits of both semantic-dictionary mapping as well as unsupervised learning. Using the vector representation, we automatically classify the radiology reports into three classes denoting confidence in the diagnosis of intracranial hemorrhage by the interpreting radiologist. We performed experiments with varying hyperparameter settings of the word embeddings and a range of different classifiers. Best performance achieved was a weighted precision of 88% and weighted recall of 90%. Our work offers the potential to leverage unstructured electronic health record data by allowing direct analysis of narrative clinical notes.
Indexed as
Identifiers
29854105PMC5977573W2769992556What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.