Automated Screening of Patients for Dietician Referral

2020 ◽  
pp. 319-325
Author(s):  
Kamran Soomro ◽  
Elias Pimenidis
Keyword(s):  
Automated Screening

Ultramicro Automated Screening Method for Uric Acid

1967 ◽  
Vol 13 (11) ◽  
pp. 985-993 ◽  
Author(s):  
Ronald H Laessig ◽  
Chester E Underwood ◽  
Barbara J Basteyns
Keyword(s):  
Uric Acid ◽  
Phosphotungstic Acid ◽  
Screening Method ◽  
Sampling Procedure ◽  
Blood Capillary ◽  
Acid Complex ◽  
Blood Uric Acid ◽  
Precision And Accuracy ◽  
Automated Screening

Abstract An automated colorimetric microprocedure, suitable for screening purposes, has been developed for the determination of blood uric acid levels. The method uses 2O-µl. whole-blood (capillary) samples and is based on the AutoAnalyzer measurement of the absorbance of the colored uric acid-phosphotungstic acid complex. The dilution inherent in the sampling procedure necessitated a modification of the existing AutoAnalyzer method to increase the sensitivity. The proposed method is evaluated for precision and accuracy by comparison with the standard AutoAnalyzer macro-method.

scholarly journals Correction: A High-Content Assay Enables the Automated Screening and Identification of Small Molecules with Specific ALDH1A1-Inhibitory Activity

PLoS ONE ◽  
2018 ◽  
Vol 13 (5) ◽  
pp. e0197292 ◽  
Author(s):  
Adam Yasgar ◽  
Steven A. Titus ◽  
Yuhong Wang ◽  
Carina Danchik ◽  
Shyh-Ming Yang ◽  
...  
Keyword(s):  
Small Molecules ◽  
Inhibitory Activity ◽  
Screening And Identification ◽  
Automated Screening

scholarly journals Evaluation of a New Immunochromatography Technology Test (LDBio Diagnostics) To Detect Toxoplasma IgG and IgM: Comparison with the Routine Architect Technique

2017 ◽  
Vol 55 (12) ◽  
pp. 3395-3404 ◽  
Author(s):  
Caroline Mahinc ◽  
Pierre Flori ◽  
Edouard Delaunay ◽  
Cécile Guillerme ◽  
Sana Charaoui ◽  
...  
Keyword(s):  
Western Blot ◽  
Sensitivity And Specificity ◽  
Blot Analysis ◽  
False Positive ◽  
Automated System ◽  
University Hospitals ◽  
Content Type ◽  
Automated Screening ◽  
Commercial Kits ◽  
Fully Automated System

ABSTRACTA study comparing the ICT (immunochromatography technology)ToxoplasmaIgG and IgM rapid diagnostic test (LDBio Diagnostics, France) with a fully automated system, Architect, was performed on samples from university hospitals of Marseille and Saint-Etienne. A total of 767 prospective sera and 235 selected sera were collected. The panels were selected to test various IgG and IgM parameters. The reference technique,ToxoplasmaIgGII Western blot analysis (LDBio Diagnostics), was used to confirm the IgG results, and commercial kits Platelia Toxo IgM (Bio-Rad) and Toxo-ISAgA (bioMérieux) were used in Saint-Etienne and Marseille, respectively, as the IgM reference techniques. Sensitivity and specificity of the ICT and the Architect IgG assays were compared using a prospective panel. Sensitivity was 100% for the ICT test and 92.1% for Architect (cutoff at 1.6 IU/ml). The low-IgG-titer serum results confirmed that ICT sensitivity was superior to that of Architect. Specificity was 98.7% (ICT) and 99.8% (Architect IgG). The ICT test is also useful for detecting IgM without IgG and is both sensitive (100%) and specific (100%), as it can distinguish nonspecific IgM from specificToxoplasmaIgM. In comparison, IgM sensitivity and specificity on Architect are 96.1% and 99.6%, respectively (cutoff at 0.5 arbitrary units [AU]/ml). To conclude, this new test overcomes the limitations of automated screening techniques, which are not sensitive enough for IgG and lack specificity for IgM (rare IgM false-positive cases).

Use of a crystallization robot to set up sitting-drop vapor-diffusion crystallization andin situcrystallization screens

2000 ◽  
Vol 33 (2) ◽  
pp. 344-349 ◽  
Author(s):  
Christopher F. Snook ◽  
Michael D. Purdy ◽  
Michael C. Wiener
Keyword(s):  
Membrane Proteins ◽  
Protein Crystallization ◽  
Integral Membrane Proteins ◽  
Vapor Diffusion ◽  
Liquid Handling ◽  
General Utility ◽  
Crystallization Experiments ◽  
Automated Screening ◽  
Set Up

A commercial crystallization robot has been modified for use in setting up sitting-drop vapor-diffusion crystallization experiments, and for setting up protein crystallization screensin situ. The primary aim of this effort is the automated screening of crystallization of integral membrane proteins in detergent-containing solutions. However, the results of this work are of general utility to robotic liquid-handling systems. Sources of error that can prevent the accurate dispensing and mixing of solutions have been identified, and include local environmental, machine-specific and solution conditions. Solutions to each of these problems have been developed and implemented.

scholarly journals Towards automated screening of two-dimensional crystals

2007 ◽  
Vol 160 (3) ◽  
pp. 324-331 ◽  
Author(s):  
Anchi Cheng ◽  
Albert Leung ◽  
Denis Fellmann ◽  
Joel Quispe ◽  
Christian Suloway ◽  
...  
Keyword(s):  
Two Dimensional ◽  
Automated Screening

Epileptic Seizure Prediction Using Deep Transformer Model

2021 ◽  
Author(s):  
Abhijeet Bhattacharya ◽  
Tanmay Baweja ◽  
S. P. K. Karri
Keyword(s):  
Signal Processing ◽  
Deep Learning ◽  
False Positive Rate ◽  
Superior Performance ◽  
Seizure Prediction ◽  
Advantages And Disadvantages ◽  
Positive Rate ◽  
Benchmark Datasets ◽  
Automated Screening ◽  
Transformer Model

The electroencephalogram (EEG) is the most promising and efficient technique to study epilepsy and record all the electrical activity going in our brain. Automated screening of epilepsy through data-driven algorithms reduces the manual workload of doctors to diagnose epilepsy. New algorithms are biased either towards signal processing or deep learning, which holds subjective advantages and disadvantages. The proposed pipeline is an end-to-end automated seizure prediction framework with a Fourier transform feature extraction and deep learning-based transformer model, a blend of signal processing and deep learning — this imbibes the potential features to automatically identify the attentive regions in EEG signals for effective screening. The proposed pipeline has demonstrated superior performance on the benchmark dataset with average sensitivity and false-positive rate per hour (FPR/h) as 98.46%, 94.83% and 0.12439, 0, respectively. The proposed work shows great results on the benchmark datasets and a big potential for clinics as a support system with medical experts monitoring the patients.

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