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Radiology Information Systems

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Comparison Between Manual Auditing and a Natural Language Process With Machine Learning Algorithm to Evaluate Faculty Use of Standardized Reports in Radiology.

Journal of the American College of Radiology : JACR
PURPOSE: When implementing or monitoring department-sanctioned standardized radiology reports, feedback about individual faculty performance has been shown to be a useful driver of faculty compliance. Most commonly, these data are derived from manual...

Automated Reconciliation of Radiology Reports and Discharge Summaries.

AMIA ... Annual Symposium proceedings. AMIA Symposium
We study machine learning techniques to automatically identify limb abnormalities (including fractures, dislocations and foreign bodies) from radiology reports. For patients presenting to the Emergency Room (ER) with suspected limb abnormalities (e.g...

Automatic abstraction of imaging observations with their characteristics from mammography reports.

Journal of the American Medical Informatics Association : JAMIA
BACKGROUND: Radiology reports are usually narrative, unstructured text, a format which hinders the ability to input report contents into decision support systems. In addition, reports often describe multiple lesions, and it is challenging to automati...

A natural language processing pipeline for pairing measurements uniquely across free-text CT reports.

Journal of biomedical informatics
OBJECTIVE: To standardize and objectivize treatment response assessment in oncology, guidelines have been proposed that are driven by radiological measurements, which are typically communicated in free-text reports defying automated processing. We st...

Improved medical image modality classification using a combination of visual and textual features.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
In this paper, we present the approach that we applied to the medical modality classification tasks at the ImageCLEF evaluation forum. More specifically, we used the modality classification databases from the ImageCLEF competitions in 2011, 2012 and ...

Multimodal medical information retrieval with unsupervised rank fusion.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Modern medical information retrieval systems are paramount to manage the insurmountable quantities of clinical data. These systems empower health care experts in the diagnosis of patients and play an important role in the clinical decision process. H...

Comparing fusion techniques for the ImageCLEF 2013 medical case retrieval task.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Retrieval systems can supply similar cases with a proven diagnosis to a new example case under observation to help clinicians during their work. The ImageCLEFmed evaluation campaign proposes a framework where research groups can compare case-based re...

Evaluating performance of biomedical image retrieval systems--an overview of the medical image retrieval task at ImageCLEF 2004-2013.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Medical image retrieval and classification have been extremely active research topics over the past 15 years. Within the ImageCLEF benchmark in medical image retrieval and classification, a standard test bed was created that allows researchers to com...