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Description
The Cambridge Neuropsychological Test Automated Battery (CANTAB), which was initially created at the University of Cambridge, provides highly accurate and objective assessments of cognitive abilities that are linked to neural networks. With the capability to detect variations in neuropsychological performance, CANTAB encompasses a wide array of tests that evaluate working memory, learning, and executive function, as well as visual, verbal, and episodic memory; attention, information processing, and reaction time; social and emotional recognition, decision-making, and response control. These cognitive evaluations serve as crucial instruments for unraveling the complexities of specific brain functions associated with various disorders and conditions, offering valuable insights into their underlying causes, facilitating the early detection of symptoms, and assessing the impact of interventions aimed at enhancing brain health. By utilizing the CANTAB, researchers and clinicians can better understand cognitive impairments, leading to more effective strategies for treatment and support.
Description
The Microsoft Cognitive Toolkit (CNTK) is an open-source framework designed for high-performance distributed deep learning applications. It represents neural networks through a sequence of computational operations organized in a directed graph structure. Users can effortlessly implement and integrate various popular model architectures, including feed-forward deep neural networks (DNNs), convolutional neural networks (CNNs), and recurrent neural networks (RNNs/LSTMs). CNTK employs stochastic gradient descent (SGD) along with error backpropagation learning, enabling automatic differentiation and parallel processing across multiple GPUs and servers. It can be utilized as a library within Python, C#, or C++ applications, or operated as an independent machine-learning tool utilizing its own model description language, BrainScript. Additionally, CNTK's model evaluation capabilities can be accessed from Java applications, broadening its usability. The toolkit is compatible with 64-bit Linux as well as 64-bit Windows operating systems. For installation, users have the option of downloading pre-compiled binary packages or building the toolkit from source code available on GitHub, which provides flexibility depending on user preferences and technical expertise. This versatility makes CNTK a powerful tool for developers looking to harness deep learning in their projects.
API Access
Has API
API Access
Has API
Integrations
AI Skills Navigator
Alteryx
AssurX
AuraQuantic
Azure Data Science Virtual Machines
Azure Database for MariaDB
Microsoft Dynamics 365 Finance
Microsoft Dynamics Supply Chain Management
Microsoft Power Platform
Integrations
AI Skills Navigator
Alteryx
AssurX
AuraQuantic
Azure Data Science Virtual Machines
Azure Database for MariaDB
Microsoft Dynamics 365 Finance
Microsoft Dynamics Supply Chain Management
Microsoft Power Platform
Pricing Details
No price information available.
Free Trial
Free Version
Pricing Details
No price information available.
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
Cambridge Cognition
Founded
2002
Country
United Kingdom
Website
www.cambridgecognition.com
Vendor Details
Company Name
Microsoft
Founded
1975
Country
United States
Website
docs.microsoft.com/en-us/cognitive-toolkit/
Product Features
Clinical Trial Management
21 CFR Part 11 Compliance
Document Management
Electronic Data Capture
Enrollment Management
HIPAA Compliant
Monitoring
Patient Database
Recruiting Management
Scheduling
Study Planning
Product Features
Deep Learning
Convolutional Neural Networks
Document Classification
Image Segmentation
ML Algorithm Library
Model Training
Neural Network Modeling
Self-Learning
Visualization
