3 resultados para Technology assessment.


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This study is part of an ongoing collaborative effort between the medical and the signal processing communities to promote research on applying standard Automatic Speech Recognition (ASR) techniques for the automatic diagnosis of patients with severe obstructive sleep apnoea (OSA). Early detection of severe apnoea cases is important so that patients can receive early treatment. Effective ASR-based detection could dramatically cut medical testing time. Working with a carefully designed speech database of healthy and apnoea subjects, we describe an acoustic search for distinctive apnoea voice characteristics. We also study abnormal nasalization in OSA patients by modelling vowels in nasal and nonnasal phonetic contexts using Gaussian Mixture Model (GMM) pattern recognition on speech spectra. Finally, we present experimental findings regarding the discriminative power of GMMs applied to severe apnoea detection. We have achieved an 81% correct classification rate, which is very promising and underpins the interest in this line of inquiry.

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Abstract A prospective 1-year follow-up study in ear, nose, and throat (ENT) cancer patients was carried out one year after radiotherapy to assess the effect of varying consumption of ω3 fatty acid according to whether they consumed more or less than the 50th percentile of ω3 fatty acids. Clinical, analytical, inflammatory (CRP and IL-6), and oxidative variables (TAC, GPx, GST, and SOD) were evaluated. The study comprised 31 patients (87.1% men), with a mean age of 61.3 ± 9.1 years. Hematological variables showed significant differences in the patients with a lower consumption of ω3 fatty acids. A lower mortality and longer survival were found in the group with ω3 fatty acid consumption ≥50th percentile but the differences were not significant. No significant difference was reached in toxicity, inflammation, and oxidative stress markers. The group with ω3 fatty acid consumption <50th percentile significantly experienced more hematological and immune changes.

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This paper addresses a fully automatic landmarks detection method for breast reconstruction aesthetic assessment. The set of landmarks detected are the supraesternal notch (SSN), armpits, nipples, and inframammary fold (IMF). These landmarks are commonly used in order to perform anthropometric measurements for aesthetic assessment. The methodological approach is based on both illumination and morphological analysis. The proposed method has been tested with 21 images. A good overall performance is observed, although several improvements must be achieved in order to refine the detection of nipples and SSNs.