10 research outputs found

    Presence of papillomavirus-like DNA sequences in cutaneous fibropapillomas of the goat udder.

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    Remote mobile manipulation with the centauro robot : Full‐body telepresence and autonomous operator assistance

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    Solving mobile manipulation tasks in inaccessible and dangerous environments is an important application of robots to support humans. Example domains are construction and maintenance of manned and unmanned stations on the moon and other planets. Suitable platforms require flexible and robust hardware, a locomotion approach that allows for navigating a wide variety of terrains, dexterous manipulation capabilities, and respective user interfaces. We present the CENTAURO system which has been designed for these requirements and consists of the Centauro robot and a set of advanced operator interfaces with complementary strength enabling the system to solve a wide range of realistic mobile manipulation tasks. The robot possesses a centaur-like body plan and is driven by torque-controlled compliant actuators. Four articulated legs ending in steerable wheels allow for omnidirectional driving as well as for making steps. An anthropomorphic upper body with two arms ending in five-finger hands enables human-like manipulation. The robot perceives its environment through a suite of multimodal sensors. The resulting platform complexity goes beyond the complexity of most known systems which puts the focus on a suitable operator interface. An operator can control the robot through a telepresence suit, which allows for flexibly solving a large variety of mobile manipulation tasks. Locomotion and manipulation functionalities on different levels of autonomy support the operation. The proposed user interfaces enable solving a wide variety of tasks without previous task-specific training. The integrated system is evaluated in numerous teleoperated experiments that are described along with lessons learned

    COVID-19 Mortality Prediction From Deep Learning in a Large Multistate Electronic Health Record and Laboratory Information System Data Set: Algorithm Development and Validation

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    BackgroundCOVID-19 is caused by the SARS-CoV-2 virus and has strikingly heterogeneous clinical manifestations, with most individuals contracting mild disease but a substantial minority experiencing fulminant cardiopulmonary symptoms or death. The clinical covariates and the laboratory tests performed on a patient provide robust statistics to guide clinical treatment. Deep learning approaches on a data set of this nature enable patient stratification and provide methods to guide clinical treatment. ObjectiveHere, we report on the development and prospective validation of a state-of-the-art machine learning model to provide mortality prediction shortly after confirmation of SARS-CoV-2 infection in the Mayo Clinic patient population. MethodsWe retrospectively constructed one of the largest reported and most geographically diverse laboratory information system and electronic health record of COVID-19 data sets in the published literature, which included 11,807 patients residing in 41 states of the United States of America and treated at medical sites across 5 states in 3 time zones. Traditional machine learning models were evaluated independently as well as in a stacked learner approach by using AutoGluon, and various recurrent neural network architectures were considered. The traditional machine learning models were implemented using the AutoGluon-Tabular framework, whereas the recurrent neural networks utilized the TensorFlow Keras framework. We trained these models to operate solely using routine laboratory measurements and clinical covariates available within 72 hours of a patient’s first positive COVID-19 nucleic acid test result. ResultsThe GRU-D recurrent neural network achieved peak cross-validation performance with 0.938 (SE 0.004) as the area under the receiver operating characteristic (AUROC) curve. This model retained strong performance by reducing the follow-up time to 12 hours (0.916 [SE 0.005] AUROC), and the leave-one-out feature importance analysis indicated that the most independently valuable features were age, Charlson comorbidity index, minimum oxygen saturation, fibrinogen level, and serum iron level. In the prospective testing cohort, this model provided an AUROC of 0.901 and a statistically significant difference in survival (P<.001, hazard ratio for those predicted to survive, 95% CI 0.043-0.106). ConclusionsOur deep learning approach using GRU-D provides an alert system to flag mortality for COVID-19–positive patients by using clinical covariates and laboratory values within a 72-hour window after the first positive nucleic acid test result

    Children with special health care needs attending emergency department in Italy: analysis of 3479 cases

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    Background: Although children with special health care needs (CSHCN) represent a minority of the population, they go through more hospitalizations, more admissions to the Emergency Department (ED), and receive a major number of medical prescriptions, in comparison to general pediatric population. Objectives of the study were to determine the reasons for admission to the ED in Italian CSHCN, and to describe the association between patient\u2019s demographic data, clinical history, and health services requirements. Methods: Ad hoc web site was created to collect retrospective data of 3479 visits of CSHCN to the ED in 58 Italian Hospitals. Results: Seventy-two percent of patients admitted to ED were affected by a previously defined medical condition. Most of the ED admissions were children with syndromic conditions (54%). 44.2% of the ED admissions were registered during the night-time and/or at the weekends. The hospitalization rate was of 45.6% among patients admitted to the ED. The most common reason for admission to the ED was the presence of respiratory symptoms (26.6%), followed by gastrointestinal problems (21.3%) and neurological disorders (18.2%). 51.4% of the access were classified as \u2018urgent\u2019, with a red/yellow triage code. Considering the type of ED, 61.9% of the visits were conducted at the Pediatric EDs (PedEDs), 33.5% at the Functional EDs (FunEDs) and 4.6% at the Dedicated EDs (DedEDs). Patients with more complex clinical presentation were more likely to be evaluated at the PedEDs. CSHCN underwent to a higher number of medical procedures at the PedEDs, more in comparison to other EDs. Children with medical devices were directed to a PedED quite exclusively when in need for medical attention. Subjects under multiple anti-epileptic drug therapy attended to PedEDs or FunEDs generally. Patients affected by metabolic diseases were more likely to look for medical attention at FunEDs. Syndromic patients mostly required medical attention at the DedEDs. Conclusions: Access of CSHCN to an ED is not infrequent. For this reason, it is fundamental for pediatricians working in any kind of ED to increase their general knowledge about CHSCN and to gain expertise in the management of such patients and their related medical complexity

    Intravenous NPA for the treatment of infarcting myocardium early: InTIME-II, a double-blind comparison on of single-bolus lanoteplase vs accelerated alteplase for the treatment of patients with acute myocardial infarction

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    Aims to compare the efficacy and safety of lanoteplase, a single-bolus thrombolytic drug derived from alteplase tissue plasminogen activator, with the established accelerated alteplase regimen in patients presenting within 6 h of onset of ST elevation acute myocardial infarction. Methods and Results 15 078 patients were recruited from 855 hospitals worldwide and randomized in a 2:1 ratio to receive either lanoteplase 120 KU. kg-1 as a single intravenous bolus, or up to 100 mg accelerated alteplase given over 90 min. The primary end-point was all-cause mortality at 30 days and the hypothesis was that the two treatments would be equivalent. By 30 days, 6.61% of alteplase-treated patients and 6.75% lanoteplase-treated patients had died (relative risk 1.02). Total stroke occurred in 1.53% alteplase- and 1.87% lanoteplase-treated patients (ns); haemorrhagic stroke rates were 0.64% alteplase and 1.12% lanoteplase (P=0.004). The net clinical deficit of 30-day death or non-fatal disabling stroke was 7.0% and 7.2%, respectively. By 6 months, 8.8% of alteplase-treated patients and 8.7% of lanoteplase-treated patients had died. Conclusion Single-bolus weight-adjusted lanoteplase is an effective thrombolytic agent, equivalent to alteplase in terms of its impact on survival and with a comparable risk-benefit profile. The single-bolus regimen should shorten symptoms to treatment times and be especially convenient for emergency department or out-of-hospital administration. (C) 2000 The European Society of Cardiology
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