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What is annalise.ai?

By reviewing up to three images for each case, which include both frontal and lateral views, medical professionals can significantly improve their diagnostic accuracy by linking insights gained from different perspectives. The development of Annalise CXR’s comprehensive ontology tree was informed by clinical experience, aiming to compile an exhaustive list of findings that are vital and advantageous for healthcare providers. Crafted by clinicians who understand the importance of a seamless workflow, Annalise CXR features a versatile user interface that integrates effortlessly with existing PACS and RIS systems. Physicians can begin utilizing Annalise CXR in under ten minutes, thereby greatly minimizing the learning curve associated with new technologies. Additionally, the confidence bar feature provides insights into the likelihood of a finding and the uncertainty surrounding the AI model, allowing clinicians to interpret the results with enhanced certainty. This cutting-edge methodology not only simplifies the diagnostic workflow but also contributes to improved clinical decision-making processes, ultimately leading to better patient outcomes. As a result, healthcare professionals are equipped with powerful tools to deliver more accurate diagnoses efficiently.

What is Merlin CardioMotion?

Merlin's CardioMotionTM echo analysis and reporting software, distributed by CDN in Australia, transforms the approach to quickly diagnosing cardiac issues. It is specifically tailored for use in various medical environments such as emergency departments, CCUs, ICUs, oncology suites, medical center practitioners, ultrasound labs, cardiology sections, and even in rural or isolated areas where point-of-care devices are essential. Additionally, it offers significant benefits for cardiac monitoring in clinical trials. What distinguishes Merlin CardioMotionTM is its unique capability to accurately process slow frame rate echo clips without requiring an ECG trace for detection, thus making it usable with lower-end ultrasound machines. Utilizing advanced image processing technology, the software is grounded in proprietary algorithms that enable the automatic detection of the ventricular wall and its borders. This cutting-edge methodology facilitates a rapid and accurate quantitative assessment of the heart's dynamic performance, leading to improved patient care and outcomes. Consequently, healthcare providers are empowered to make better-informed decisions regarding cardiac health management, ultimately promoting a higher standard of patient well-being.

Media

Media

Integrations Supported

Additional information not provided

Integrations Supported

Additional information not provided

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

annalise.ai

Date Founded

2019

Company Location

Australia

Company Website

annalise.ai/

Company Facts

Organization Name

Central Data Networks

Company Location

Australia

Company Website

www.cdnpacs.com/cardiology/cardiac-analysis/cardiomotion/

Categories and Features

Medical Imaging

Automated Routing
Comparison View
Compliance Management
Data Import / Export
Diagnostic Reporting
Image Analytics
Treatment Planning
Workflow Management

Categories and Features

Medical Imaging

Automated Routing
Comparison View
Compliance Management
Data Import / Export
Diagnostic Reporting
Image Analytics
Treatment Planning
Workflow Management

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