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What is Evorad?

Evorad presents a comprehensive enterprise imaging solution that seamlessly merges the management, viewing, reporting, collaboration, and patient accessibility of medical images into a single, secure, and scalable environment, effectively integrating PACS (Picture Archiving and Communication System) with zero-footprint diagnostic viewing, characterized by rapid load times, structured reporting, collaborative functionalities, and customizable AI-driven workflows that empower radiology teams to deliver faster and more accurate diagnoses. The platform complies with industry standards including DICOM, DICOMweb, and HL7, ensuring excellent interoperability with existing EHR/RIS/HIS systems, while providing a vendor-neutral archive that assures data portability, regulatory compliance, and secure long-term storage options. Evorad's versatile implementation capabilities support cloud, hybrid, or on-premise configurations, featuring tiered storage solutions and strong uptime management for optimal performance. Furthermore, Evorad incorporates advanced functionalities such as browser-based 3D visualization, intelligent worklists, automated queue balancing, and effective tools for aligning study metadata, facilitating easy access to prior images when necessary. Ultimately, Evorad is designed to significantly improve the workflow of medical imaging professionals by delivering an all-encompassing and intuitive platform that meets their diverse needs. This dedication to innovation ultimately aims to transform the landscape of medical imaging in a meaningful way.

What is AWS HealthImaging?

AWS HealthImaging is specifically designed for developers focused on creating cloud-based solutions for medical imaging. This service is capable of processing DICOM P10 format data and provides APIs that enable swift retrieval and tailored storage options. Users can significantly reduce costs by up to 40% through advanced compression methods while keeping a single copy of each image in the cloud. The platform ensures incredibly fast access to medical imaging data, achieving subsecond latency from nearly any location thanks to its robust cloud-native APIs and applications. By taking care of infrastructure management challenges, teams can dedicate their resources to delivering superior patient care. HealthImaging enjoys support from leading medical imaging vendors, guaranteeing seamless integration with cloud-native workflows. Users can effectively store and stream medical images directly from AWS, benefiting from both low-latency performance and high availability. Additionally, organizations can optimize long-term archival costs while ensuring quick image retrieval. The platform also supports artificial intelligence and machine learning for processing imaging archives, further enhancing its capabilities with a range of tools and services. This innovative approach is transforming how medical data is managed and utilized, paving the way for more efficient healthcare solutions. In this way, AWS HealthImaging not only meets current industry needs but also anticipates future developments in medical imaging technology.

Media

Media

Integrations Supported

Integrations Supported

Amazon Web Services (AWS)

API Availability

API Availability

Has API

Pricing Information

Pricing not provided

Pricing Information

$0.105 per month
Free Trial Offered?

Supported Platforms

SaaS

Supported Platforms

SaaS

Customer Service / Support

Standard Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Online Training

Training Options

Documentation Hub
Webinars
On-Site Training

Company Facts

Organization Name

IKnowHealth

Date Founded

2023

Company Location

Greece

Company Website

www.evorad.com

Company Facts

Organization Name

Amazon

Date Founded

1994

Company Location

United States

Company Website

aws.amazon.com/healthimaging/

Categories and Features

Medical Imaging

Not specified

PACS

Not specified

Categories and Features

Medical Imaging

Not specified

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