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What is Iris.ai?

At Iris.ai, we have dedicated the past six years to developing an award-winning AI engine that excels in comprehending scientific texts. Our state-of-the-art algorithms for text similarity, extraction of tabular data, learning domain-specific entity representations, and entity disambiguation and linking rank among the finest globally. Additionally, our machine constructs an extensive knowledge graph that encompasses all entities and their interconnections, enabling users to learn from it, utilize it, and also provide feedback to enhance the system further. The Iris.ai Researcher Workspace offers a versatile suite of tools that enables users to tackle projects from multiple perspectives. Its modules feature content-driven exploratory searches, analytical assessments of document collections, systematic extraction and organization of data points, automated summarization of various documents, and highly effective filters based on context descriptions, machine analyses, or targeted data points and entities. Furthermore, the Iris.ai engine for scientific text understanding is a robust interdisciplinary platform that can be automatically fine-tuned for specific research domains, allowing for a deeper machine comprehension without the need for human training or annotation, ultimately streamlining the research process.

What is Amazon Comprehend Medical?

Amazon Comprehend Medical is an NLP service designed to adhere to HIPAA standards, employing machine learning to extract health information from medical documents without necessitating any prior expertise in machine learning from its users. A vast amount of healthcare data is found in unstructured formats, such as physicians' notes, clinical trial reports, and patient histories. Relying on traditional, manual methods for data extraction is not only time-consuming but also prone to errors, as rule-based automation often fails to capture essential contextual details, resulting in incomplete data retrieval. This lack of reliability can significantly undermine the effectiveness of large-scale analytics, which are critical for advancements in the healthcare and life sciences industries, ultimately impeding potential enhancements in patient care and operational effectiveness. By utilizing this sophisticated service, healthcare organizations can gain invaluable insights and improve their decision-making capabilities, ultimately leading to better outcomes for patients. This transformative approach represents a significant leap forward in how health data can be leveraged for greater efficiency and efficacy in medical practices.

Media

Media

Integrations Supported

Integrations Supported

AWS AI Services
AWS App Mesh
Amazon Comprehend

API Availability

API Availability

Has API

Pricing Information

Pricing not provided

Pricing Information

Pricing not provided

Supported Platforms

SaaS

Supported Platforms

SaaS

Customer Service / Support

Web-Based Support

Customer Service / Support

Web-Based Support

Training Options

Webinars

Training Options

Documentation Hub

Company Facts

Organization Name

Iris.ai

Date Founded

2015

Company Location

Norway

Company Website

iris.ai/

Company Facts

Organization Name

Amazon

Date Founded

1994

Company Location

United States

Company Website

aws.amazon.com/comprehend/medical/

Categories and Features

AI Science

Not specified

Data Extraction

Not specified

Categories and Features

Data Extraction

Not specified

Healthcare AI

Not specified

Healthcare APIs

Not specified

Life Sciences

Not specified

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