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Patient-centered radiology reports with generative artificial intelligence: adding value to radiology reporting
The purposes were to assess the efficacy of AI-generated radiology reports in terms of report summary, patient-friendliness, and recommendations and...
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Can ChatGPT write radiology reports?
These case examples exemplify the utility of ChatGPT in augmenting the radiology report drafting process, thereby contributing to the efficiency of...
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Patterns of Access to Radiology Reports and Images Through a Patient Portal
Access to radiology reports and images through a patient portal offers several advantages. The purpose of this study was to characterize patient’s...
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Utilizing Longitudinal Chest X-Rays and Reports to Pre-fill Radiology Reports
Despite the reduction in turn-around times in radiology reporting with the use of speech recognition software, persistent communication errors can...
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Using BERT models for breast cancer diagnosis from Turkish radiology reports
Diagnostic radiology is concerned with obtaining images of the internal organs using radiological imaging procedures. These images are then...
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Translating musculoskeletal radiology reports into patient-friendly summaries using ChatGPT-4
ObjectiveTo assess the feasibility of using large language models (LLMs), specifically ChatGPT-4, to generate concise and accurate layperson...
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ChatGPT makes medicine easy to swallow: an exploratory case study on simplified radiology reports
ObjectivesTo assess the quality of simplified radiology reports generated with the large language model (LLM) ChatGPT and to discuss challenges and...
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Evaluating the performance of Generative Pre-trained Transformer-4 (GPT-4) in standardizing radiology reports
ObjectiveRadiology reporting is an essential component of clinical diagnosis and decision-making. With the advent of advanced artificial intelligence...
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Clinical Concept-Based Radiology Reports Classification Pipeline for Lung Carcinoma
Rising incidence and mortality of cancer have led to an incremental amount of research in the field. To learn from preexisting data, it has become...
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SimpleRad: Patient-Friendly Dutch Radiology Reports
Patients increasingly have access to their electronic health records. However, much of the content therein is not specifically written for them;...
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Extracting Pulmonary Nodules and Nodule Characteristics from Radiology Reports of Lung Cancer Screening Patients Using Transformer Models
Pulmonary nodules and nodule characteristics are important indicators of lung nodule malignancy. However, nodule information is often documented as...
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MeFormer: Generating Radiology Reports via Memory Enhanced Pretraining Transformer
Writing a radiology image report is a very time-consuming and tedious task. Using AI to generate the report is an efficient approach, but there are...
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ClotCatcher: a novel natural language model to accurately adjudicate venous thromboembolism from radiology reports
IntroductionAccurate identification of venous thromboembolism (VTE) is critical to develop replicable epidemiological studies and rigorous...
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Turning radiology reports into epidemiological data to track seasonal pulmonary infections and the COVID-19 pandemic
ObjectivesTo automatically label chest radiographs and chest CTs regarding the detection of pulmonary infection in the report text, to calculate the...
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Application program to detect unrecognized information regarding malignant tumors in radiology reports
PurposeAccurate disease diagnosis from radiology reports is important in medical treatment. Preventing physicians from overlooking the findings of...
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Deep learning-based detection of patients with bone metastasis from Japanese radiology reports
PurposeDeep learning (DL) is a state-of-the-art technique for develo** artificial intelligence in various domains and it improves the performance...
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A novel reporting workflow for automated integration of artificial intelligence results into structured radiology reports
ObjectivesArtificial intelligence (AI) has tremendous potential to help radiologists in daily clinical routine. However, a seamless, standardized,...
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Knowledge Graph Embeddings for Multi-lingual Structured Representations of Radiology Reports
The way we analyse clinical texts has undergone major changes over the last years. The introduction of language models such as BERT led to...
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Natural language processing to predict isocitrate dehydrogenase genotype in diffuse glioma using MR radiology reports
ObjectivesTo evaluate the performance of natural language processing (NLP) models to predict isocitrate dehydrogenase (IDH) mutation status in...
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Patient Understanding of Oncologic Radiology Reports: Is Access to Electronic Medical Records Helpful?
Access to electronic medical record (EMR) patient portals made it easier for patients to quickly acquire the results of their radiology studies....
