Controller design and consonantal contrast coding using a multi-finger tactual display. (25/76)

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Interactive voice response systems for improving delivery of ambulatory care. (26/76)

OBJECTIVE: To comprehensively describe the populations, interventions, and outcomes of interactive voice response system (IVRS) clinical trials. METHODS: We identified studies using MEDLINE (1950-2008) and EMBASE (1980-2008). We also identified studies using hand searches of the Science Citation Index and the reference lists of included articles. Included were randomized and controlled clinical trials that examined the effect of an IVRS intervention on clinical end points, measures of disease control, process adherence, or quality-of-life measures. Continuous and dichotomous outcomes were meta-analyzed using mean difference and median effects methodology, respectively. RESULTS: Forty studies (n = 106,959 patients) met inclusion criteria. Of these studies, 25 used an IVRS intervention aimed at encouraging adherence with recommended tests, treatments, or behaviors; the remaining 15 used an IVRS for chronic disease management. Three studies reported clinical end points, which could not be statistically pooled. In 6 studies that reported objective clinical measures of disease control (glycosylated hemoglobin, total cholesterol, and serum glucose), the IVRS was associated with nonsignificant improvements. In 14 studies that measured objective process adherence outcomes, the median effect was 7.9% (25th-75th percentile: 2.8%, 19.5%). For the 16 studies that assessed patient-reported measures of disease control and the 11 studies that assessed patient-reported process adherence outcomes, approximately one-third of the outcomes significantly favored the IVRS group. CONCLUSION: IVRS interventions, which enable patients to interact with computer databases via telephone, have shown a significant benefit in adherence to various processes of care. Future IVRS studies should include clinically relevant outcomes.  (+info)

KIDMAP, a web based system for gathering patients' feedback on their doctors. (27/76)

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Development of an automated speech recognition interface for Personal Emergency Response Systems. (28/76)

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Recognizing sequences of sequences. (29/76)

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The challenges, opportunities, and imperative of structured reporting in medical imaging. (30/76)

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An intelligent listening framework for capturing encounter notes from a doctor-patient dialog. (31/76)

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Selective-tap blind signal processing for speech separation. (32/76)

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