Sensitivity and specificity of machine learning classifiers for glaucoma diagnosis using Spectral Domain OCT and standard automated perimetry

PURPOSE: To evaluate the sensitivity and specificity of machine learning classifiers (MLCs) for glaucoma diagnosis using Spectral Domain OCT (SD-OCT) and standard automated perimetry (SAP). METHODS: Observational cross-sectional study. Sixty two glaucoma patients and 48 healthy individuals were included. All patients underwent a complete ophthalmologic examination, achromatic standard automated perimetry (SAP) and retinal nerve fiber layer (RNFL) imaging with SD-OCT (Cirrus HD-OCT; Carl Zeiss Meditec Inc., Dublin, California). Receiver operating characteristic (ROC) curves were obtained for all SD-OCT parameters and global indices of SAP. Subsequently, the following MLCs were tested using parameters from the SD-OCT and SAP: Bagging (BAG), Naive-Bayes (NB), Multilayer Perceptron (MLP), Radial Basis Function (RBF), Random Forest (RAN), Ensemble Selection (ENS), Classification Tree (CTREE), Ada Boost M1(ADA),Support Vector Machine Linear (SVML) and Support Vector Machine Gaussian (SVMG). Areas under the receiver operating characteristic curves (aROC) obtained for isolated SAP and OCT parameters were compared with MLCs using OCT+SAP data. RESULTS: Combining OCT and SAP data, MLCs' aROCs varied from 0.777(CTREE) to 0.946 (RAN).The best OCT+SAP aROC obtained with RAN (0.946) was significantly larger the best single OCT parameter (p<0.05), but was not significantly different from the aROC obtained with the best single SAP parameter (p=0.19). CONCLUSION: Machine learning classifiers trained on OCT and SAP data can successfully discriminate between healthy and glaucomatous eyes. The combination of OCT and SAP measurements improved the diagnostic accuracy compared with OCT data alone.

Can We Predict The Clinical Outcomes Of Genitourinary Trauma Patients And Offer Them An Evidence-based Support? The Case For Telemedicine Network.

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Development And Characterization Of A Cationic Lipid Nanocarrier As Non-viral Vector For Gene Therapy.

The aim of the present work was to produce a cationic solid lipid nanoparticle (SLN) as non-viral vector for protein delivery. Cationic SLN were produced by double emulsion method, composed of softisan(®) 100, cetyltrimethylammonium bromide (CTAB), Tween(®) 80, Span(®) 80, glycerol and lipoid(®) S75 loading insulin as model protein. The formulation was characterized in terms of mean hydrodynamic diameter (z-ave), polydispersity index (PI), zeta potential (ZP), stability during storage time, stability after lyophilization, effect of toxicity and transfection ability in HeLa cells, in vitro release profile and morphology. SLN were stable for 30days and showed minimal changes in their physicochemical properties after lyophilization. The particles exhibited a relatively slow release, spherical morphology and were able to transfect HeLa cells, but toxicity remained an obstacle. Results suggest that SLN are nevertheless promising for delivery of proteins or nucleic acids for gene therapy.

Matrix Support And Institutional Support: Analyzing Their Construction.

This is an analysis of the theoretical and practical construction of the methodology of Matrix Support by means of studies on Paideia Support (Institutional and Matrix Support), which is an inter-professional work of joint care in recent literature and official documents of the Unified Health System (SUS). An attempt was made to describe methodological concepts and strategies. A comparative analysis of Institutional Support and Matrix Support was also conducted using the epistemological framework of Field and Core Knowledge and Practices.

Proposta metodológica utilizando ferramentas de qualidade na avaliação do processo de pulverização

The present work aimed to create a methodology to evaluate the pulverization process with the use of quality tools. It was listed the primary factors, secondary factors, tertiary factors and, with the check list tool support, the list was elaborated. It was evaluated the factors labor, agriculture machine, material and method of 32 pulverization process before pesticide application, in that each factor received a punctuation, having as total sum of 750 points. The medium punctuation to the factors labor, agriculture machine, material and method was 78; 211; 49; 20 and 94 points, respectively. The sum of the factors points for the 32 processes, the minimum value found was 230 and maximum was 620 points. With the proposed methodology, can be identify which common causes of the processes can affect its result.

Análise cinemática tridimensional do salto em distância de atletas de alto nível em competição

Universidade Estadual de Campinas . Faculdade de Educação Física