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The detailed description here provided covers the system, the parameters identified and the testing procedure; it also includes the technical specifications of the hardware, the features introduced in the updated version of the software and the application of the system in clinical practice.The comparison of the technical considerations and clinical results with the updated literature confirmed the system’s optimal ergonomics, good reproducibility and clinical reliability.

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We also report on the use of “positional features”, a novel type of feature intended to aid in the automatic annotation of texts in which the instances of a given concept may be hypothesized to systematically occur in specific areas of the text.

We present experiments on a dataset of mammography reports in which the proposed ensemble is shown to outperform a traditional, single-stage CRFs system in two different, applicatively interesting scenarios.

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A screenshot displaying a mammographic report automatically annotated according to the nine concepts of interest.

The screenshot depicts the interface of the GATE system, which the two human annotators have used for manually annotating the reports.► Automated information extraction from radiology reports is studied.

The main purpose of this article was to describe in detail, from the perspective of the clinical end user, a previously presented non-invasive methodology, applied in the treatment of anterior cruciate ligament injury, in which inertial sensors are used to quantify the pivot shift test.

The outcomes obtained and relative considerations were compared with findings emerging from a review of the relevant updated literature.

► Experiments are run on a dataset of radiological reports.

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