Automated Labelling using an Attention model for Radiology reports of MRI scans (ALARM)
Labelling large datasets for training high-capacity neural networks is a major obstacle to the development of deep learning-based medical imaging applications. Here we present a transformer-based network for magnetic resonance imaging (MRI) radiology report classification which automates this task by assigning image labels on the basis of free-text expert radiology reports. Our model's performance is comparable to that of an expert radiologist, and better than that of an expert physician, demonstrating the feasibility of this approach. We make code available online for researchers to label their own MRI datasets for medical imaging applications.
Code (0)
등록된 구현이 없습니다.
Similar Papers 제목 키워드 기반
Automated Spinal MRI Labelling from Reports Using a Large Language Model
We propose a general pipeline to automate the extraction of labels from radiology reports using large language models, which we validate on spinal MRI reports. The efficacy of our labelling method is measured on five dis…
Language ModelingLanguage ModellingLarge Language ModelLabelling imaging datasets on the basis of neuroradiology reports: a validation study
Natural language processing (NLP) shows promise as a means to automate the labelling of hospital-scale neuroradiology magnetic resonance imaging (MRI) datasets for computer vision applications. To date, however, there ha…
Automated detection of underdiagnosed medical conditions via opportunistic imaging
Abdominal computed tomography (CT) scans are frequently performed in clinical settings. Opportunistic CT involves repurposing routine CT images to extract diagnostic information and is an emerging tool for detecting unde…
Computed Tomography (CT)DiagnosticLanguage Models for Automated Classification of Brain MRI Reports and Growth Chart Generation
Clinically acquired brain MRIs and radiology reports are valuable but underutilized resources due to the challenges of manual analysis and data heterogeneity. We developed fine-tuned language models (LMs) to classify bra…
BenchmarkingTranslating Radiology Reports into Plain Language using ChatGPT and GPT-4 with Prompt Learning: Promising Results, Limitations, and Potential
The large language model called ChatGPT has drawn extensively attention because of its human-like expression and reasoning abilities. In this study, we investigate the feasibility of using ChatGPT in experiments on using…
Language ModellingLarge Language ModelMisinformationPrompt Learning