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Deep Learning-Based Brain Hemorrhage Detection in CT Reports.

Studies in health technology and informatics
Radiology reports can potentially be used to detect critical cases that need immediate attention from physicians. We focus on detecting Brain Hemorrhage from Computed Tomography (CT) reports. We train a deep learning classifier and observe the effect...

Causal Associations Among Diseases and Imaging Findings in Radiology Reports.

Studies in health technology and informatics
This study explored the ability to identify causal relationships between diseases and imaging findings from their co-occurrences in radiology reports. A natural language processing (NLP) system with negative-expression filtering detected positive men...

Reporting guideline for the early-stage clinical evaluation of decision support systems driven by artificial intelligence: DECIDE-AI.

Nature medicine
A growing number of artificial intelligence (AI)-based clinical decision support systems are showing promising performance in preclinical, in silico evaluation, but few have yet demonstrated real benefit to patient care. Early-stage clinical evaluati...

Improvement of intervention information detection for automated clinical literature screening during systematic review.

Journal of biomedical informatics
Systematic literature review (SLR) is a crucial method for clinicians and policymakers to make their decisions in a flood of new clinical studies. Because manual literature screening in SLR is a highly laborious task, its automation by natural langua...

Natural Language Processing in Radiology: Update on Clinical Applications.

Journal of the American College of Radiology : JACR
Radiological reports are a valuable source of information used to guide clinical care and support research. Organizing and managing this content, however, frequently requires several manual curations because of the more common unstructured nature of ...

Development and Validation of a Model to Identify Critical Brain Injuries Using Natural Language Processing of Text Computed Tomography Reports.

JAMA network open
IMPORTANCE: Clinical text reports from head computed tomography (CT) represent rich, incompletely utilized information regarding acute brain injuries and neurologic outcomes. CT reports are unstructured; thus, extracting information at scale requires...

Natural Language Processing Approaches for Automated Multilevel and Multiclass Classification of Breast Lesions on Free-Text Cytopathology Reports.

JCO clinical cancer informatics
PURPOSE: The extensive growth and use of electronic health records (EHRs) and extending medical literature have led to huge opportunities to automate the extraction of relevant clinical information that helps in concise and effective clinical decisio...

Natural Language Processing Model for Identifying Critical Findings-A Multi-Institutional Study.

Journal of digital imaging
Improving detection and follow-up of recommendations made in radiology reports is a critical unmet need. The long and unstructured nature of radiology reports limits the ability of clinicians to assimilate the full report and identify all the pertine...