A systematic review of natural language processing applied to radiology reports
Background Natural language processing (NLP) has a significant role in advancing
healthcare and has been found to be key in extracting structured information from radiology …
healthcare and has been found to be key in extracting structured information from radiology …
[HTML][HTML] AMMU: a survey of transformer-based biomedical pretrained language models
KS Kalyan, A Rajasekharan, S Sangeetha - Journal of biomedical …, 2022 - Elsevier
Transformer-based pretrained language models (PLMs) have started a new era in modern
natural language processing (NLP). These models combine the power of transformers …
natural language processing (NLP). These models combine the power of transformers …
CheXbert: combining automatic labelers and expert annotations for accurate radiology report labeling using BERT
The extraction of labels from radiology text reports enables large-scale training of medical
imaging models. Existing approaches to report labeling typically rely either on sophisticated …
imaging models. Existing approaches to report labeling typically rely either on sophisticated …
[HTML][HTML] Accurate brain‐age models for routine clinical MRI examinations
DA Wood, S Kafiabadi, A Al Busaidi, E Guilhem… - Neuroimage, 2022 - Elsevier
Convolutional neural networks (CNN) can accurately predict chronological age in healthy
individuals from structural MRI brain scans. Potentially, these models could be applied …
individuals from structural MRI brain scans. Potentially, these models could be applied …
[HTML][HTML] Deep learning models for triaging hospital head MRI examinations
DA Wood, S Kafiabadi, A Al Busaidi, E Guilhem… - Medical Image …, 2022 - Elsevier
The growing demand for head magnetic resonance imaging (MRI) examinations, along with
a global shortage of radiologists, has led to an increase in the time taken to report head MRI …
a global shortage of radiologists, has led to an increase in the time taken to report head MRI …
Deep learning to automate the labelling of head MRI datasets for computer vision applications
DA Wood, S Kafiabadi, A Al Busaidi, EL Guilhem… - European …, 2022 - Springer
Objectives The purpose of this study was to build a deep learning model to derive labels
from neuroradiology reports and assign these to the corresponding examinations …
from neuroradiology reports and assign these to the corresponding examinations …
Enhancing chest X-ray datasets with privacy-preserving large language models and multi-type annotations: a data-driven approach for improved classification
In chest X-ray (CXR) image analysis, rule-based systems are usually employed to extract
labels from reports for dataset releases. However, there is still room for improvement in label …
labels from reports for dataset releases. However, there is still room for improvement in label …
A scoping review of large language model based approaches for information extraction from radiology reports
Radiological imaging is a globally prevalent diagnostic method, yet the free text contained in
radiology reports is not frequently used for secondary purposes. Natural Language …
radiology reports is not frequently used for secondary purposes. Natural Language …
[HTML][HTML] Automated data processing and feature engineering for deep learning and big data applications: a survey
A Mumuni, F Mumuni - Journal of Information and Intelligence, 2024 - Elsevier
Modern approach to artificial intelligence (AI) aims to design algorithms that learn directly
from data. This approach has achieved impressive results and has contributed significantly …
from data. This approach has achieved impressive results and has contributed significantly …
Efficient maize tassel-detection method using UAV based remote sensing
Regular monitoring is worthwhile to maintain a healthy crop. Historically, the manual
observation was used to monitor crops, which is time-consuming and often costly. The …
observation was used to monitor crops, which is time-consuming and often costly. The …