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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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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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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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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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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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Preliminary assessment of automated radiology report generation with generative pre-trained transformers: comparing results to radiologist-generated reports
PurposeIn this preliminary study, we aimed to evaluate the potential of the generative pre-trained transformer (GPT) series for generating radiology...
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Event-Based Clinical Finding Extraction from Radiology Reports with Pre-trained Language Model
Radiology reports contain a diverse and rich set of clinical abnormalities documented by radiologists during their interpretation of the images....
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Ensemble Approaches to Recognize Protected Health Information in Radiology Reports
Natural language processing (NLP) techniques for electronic health records have shown great potential to improve the quality of medical care. The...
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Enhancing the value of radiology reports: a primer for residents
PurposeThe radiology report is the primary work product of the diagnostic radiologist. Its quality is a direct reflection of his or her knowledge,...
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Investigating the impact of structured reporting on the linguistic standardization of radiology reports through natural language processing over a 10-year period
ObjectivesTo investigate how a transition from free text to structured reporting affects reporting language with regard to standardization and...
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Improved Fine-Tuning of In-Domain Transformer Model for Inferring COVID-19 Presence in Multi-Institutional Radiology Reports
Building a document-level classifier for COVID-19 on radiology reports could help assist providers in their daily clinical routine, as well as create...
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Improving case duration accuracy of orthopedic surgery using bidirectional encoder representations from Transformers (BERT) on Radiology Reports
PurposeA major source of inefficiency in the operating room is the mismatch between scheduled versus actual surgical time. The purpose of this study...
