University of Kansas

About: University of Kansas is a education organization based out in Lawrence, Kansas, United States. It is known for research contribution in the topics: Population & Poison control. The organization has 38183 authors who have published 81381 publications receiving 2986312 citations. The organization is also known as: KU & Univ of Kansas.

Real-Time Automated Detection and Quantitative Analysis of Seizures and Short-Term Prediction of Clinical Onset

Abstract: Summary: Purpose: We describe an algorithm for rapid realtime detection, quantitation, localization of seizures, and prediction of their clinical onset. Methods: Advanced digital signal processing techniques used in time-frequency localization, image processing, and identification of time-varying stochastic systems were used to develop the algorithm, which operates in generic or adaptable “modes.” The “generic mode” was tested on (a) 125 partial seizures (each contained in a 10-min segment) involving the mesial temporal regions and recorded using depth electrodes from 16 subjects, and (b) 205 ten-minute segments of randomly selected interictal (nonseizure) data. The performance of the algorithm was compared with expert visual analysis, the current “gold standard.” Results: The generic algorithm achieved perfect sensitivity and specificity (no false-positive and no false-negative detections) over the entire data set. Seizure intensity, a novel measure that seems clinically relevant, ranged between 35.7 and 6129. Detection was sufficiently rapid to allow prediction of clinical onset in 92% of seizures by a mean of 15.5 s. Conclusions: This algorithm, which was implemented with a personal computer, represents a definitive step toward rapid and accurate detection and prediction of seizures. It may also enable development of intelligent devices for automated seizure warning and treatment and stimulate new study of the dynamics of seizures and of the epileptic brain.

Juvenile localized scleroderma: clinical and epidemiological features in 750 children. An international study

Abstract: Objective. Juvenile localized scleroderma (JLS) includes a number of conditions often grouped together. With the long-term goal of developing uniform classification criteria, we studied the epidemiological, clinical and immunological features of children with JLS followed by paediatric rheumatology and dermatology centres. Methods. A large, multicentre, multinational study was conducted by collecting information on the demographics, family history, triggering environmental factors, clinical and laboratory features, and treatment of patients with JLS. Results. Seven hundred and fifty patients with JLS from 70 centres were enrolled into the study. The disease duration at diagnosis was 18 months. Linear scleroderma (LS) was the most frequent subtype (65%), followed by plaque morphea (PM) (26%), generalized morphea (GM) (7%) and deep morphea (DM) (2%). As many as 15% of patients had a mixed subtype. Ninety-one patients (12%) had a positive family history for rheumatic or autoimmune diseases; 100 (13.3%) reported environmental events as possible trigger. ANA was positive in 42.3% of the patients, with a higher prevalence in the LS-DM subtype than in the PM-GM subtype. Scl70 was detected in the sera of 3% of the patients, anticentromere antibody in 2%, anti-double-stranded DNA in 4%, anti-cardiolipin antibody in 13% and rheumatoid factor in 16%. Methotrexate was the drug most frequently used, especially during the last 5 yr. Conclusion. This study represents the largest collection of patients with JLS ever reported. The insidious onset of the disease, the delay in diagnosis, the recognition of mixed subtype and the better definition of the other subtypes should influence our efforts in educating trainees and practitioners and help in developing a comprehensive classification system for this syndrome.

Topographic solar radiation models for GIS

Abstract: Incident solar radiation at the Earth's surface is the result of a complex interaction of energy between the atmosphere and the surface Recently much progress has been made towards the creation of accurate, physically-based solar radiation formulations that can model this interaction over topographic and other surfaces (such as plant canopies) for a large range of spatial and temporal scales In this paper we summarize our current work on solar radiation models and their implementation within both GIS and image processing systems An overview of the effects of topography and plant canopies on solar radiation is presented along with a discussion of various options for obtaining the data necessary to drive specific solar radiation models Examples are given from our own work using two models, ATM (Atmospheric and Topographic Model), a model based within an image processing framework, and SOLARFLUX, a GIS-based model We consider issues of design, including GIS implementation and interface, computa