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Incredable is the first DLT-secured platform that allows you to save time, eliminate errors, and ensure your organization is compliant all in one place.
For healthcare Providers and Facilities
Incredable streamlines and simplifies the complex process of medical credentialing for hospitals and medical facilities, helping you save valuable time, reduce costs, and minimize risks. With Incredable, you can effortlessly manage all your healthcare providers and their credentials within a single, unified platform. Our state-of-the-art technology ensures top-notch data security, giving you peace of mind.
This is a MATLAB toolbox for the quality control and scoring of EMAP and SGA genetic interaction data. It includes a graphical user interface and some automatic plot-generating tools.
MATLAB Audio Database Toolbox enables easy access and filtering of audio databases such as TIMIT and YOHO by their metadata. The database toolbox comes to replace the manual filtering and custom coding usually required for accessing such databases.
The purpose of this program is to teach a computer to classify plants via their leaves. You just need to input the image of a leaf(acquired from scanner or camera), then the computer can tell you what kind of plant it is.
As a healthcare provider, you should be paid promptly for the services you provide to patients. Slow, inefficient, and error-prone manual coding keeps you from the financial peace you deserve. XpertDox’s autonomous coding solution accelerates the revenue cycle so you can focus on providing great healthcare.
Maximally flat (maxflat) digital filter design for Octave and Matlab. "Maximally flat" means that the magnitude frequency response has the maximum number of vanishing derivatives at 0 and pi. Handles arbitrary numbers of poles and zeros.
Projeny (Probablistic Networks Generator in Java) is a graphical (Java SWT) front-end to BNT (Bayes Net Toolbox for Matlab). Projeny requires BNT, JMatLink and a Matlab back-end. There is no installable release package, but source code is available on SVN - please check out from SVN to use Projeny. Projeny was started with BNJ as the base.
Implematation of robust depth-based inference tools for microarray data (a scale curve, to measure the dispersion of a set of curves, a rank test to decide if two groups of curves come from the same population, and classification techniques).
Bayesian Surprise Matlab toolkit is a basic toolkit for computing Bayesian surprise values given a large set of input samples. It is also useful as way of exploring surprise theory. For more information see also: http://ilab.usc.edu/
The Databionics ESOM Tools offer many data mining tasks using Emergent Self-Organizing Maps. Visualization, clustering, and classification of high-dimensional data using databionics principles can be performed interactively or automatically.
A collection of Matlab functions and scripts for computing the saliency map for an image, for determining the extent of a proto-object, and for serially scanning the image with the focus of attention.
An open-source package for analysis of neurophysiological data-- offline (vs real-time) processing of single-neuron spike trains or EEG data associated with behavior and memory processes. Currently MATLAB heavy, with some Windows specific code.
The class libraries here provide infrastructure for creating simulations of low energy nuclear physics experiments, as well as some useful working programs that do simple simulations and analysis of experiments performed with magnetic spectrographs.
IMAEL stands for Image Matlab Analysis and Estimation Library. It consists in a collection of functions for image filtering, analysis, visualization, for 2D, 3D grayscale and color images.
nBoost is a suite of boosting algorithms designed to solve binary classification problems on data that is not linearly separable by a convex combination of base hypotheses, i.e. noisy data. WARNING: Active development. Underlying algorithm is unstable.