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What is Deepbody Analytica?

We gather and analyze data from a wide array of sources, which includes socioeconomic variables, electronic health records, and biological samples like breath, blood, saliva, stool, urine, DNA, sweat, hair, and vital signs. This collection of health data offers valuable insights into your overall well-being. With the advent of advanced artificial intelligence, machine learning, and enhanced computational power, we are able to amalgamate information from diverse origins, providing your healthcare provider with a comprehensive view of your health risk factors. Our models are continually refined through the use of anonymized health data that is securely integrated into our database. The utilization of extensive data sets not only boosts the accuracy of our models but also significantly enhances AI's capability to detect health risks at an earlier stage compared to traditional methods, which can ultimately be life-saving. While many healthcare professionals primarily concentrate on diagnosing current health issues, our machine-learning models prioritize prevention and risk assessment, thus fostering a proactive healthcare approach. This paradigm shift enables us to identify and manage potential health challenges before they escalate into critical problems, ensuring better health outcomes for individuals. The proactive nature of our approach emphasizes the importance of early intervention in maintaining overall health.

What is Azure Text Analytics?

Harness natural language processing to gain valuable insights from unstructured text without requiring any machine learning knowledge, by utilizing an array of features from the Cognitive Services for Language. Elevate your understanding of customer emotions through sentiment analysis and identify key phrases and entities such as people, places, and organizations to uncover common themes and patterns. Use specialized, pretrained models to classify medical terminology specific to various fields. Evaluate text across multiple languages and reveal essential concepts within the content, which include key phrases and named entities that highlight individuals, events, and organizations. Delve into customer feedback regarding your brand while examining sentiments linked to specific topics through opinion mining techniques. Additionally, derive critical insights from unstructured clinical documents, including doctors' notes, electronic health records, and patient intake forms, by applying text analytics tailored for healthcare settings, ultimately enhancing patient care and informing decision-making processes. By integrating these advanced capabilities, organizations can stay ahead of trends and better meet the needs of their stakeholders.

Media

Media

Integrations Supported

Azure Marketplace
TAS Insight Engine
Unremot

Integrations Supported

Azure Marketplace
TAS Insight Engine
Unremot

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

Deepbody Analytica

Company Website

deepbody.me/

Company Facts

Organization Name

Microsoft

Date Founded

1975

Company Location

United States

Company Website

azure.microsoft.com/en-us/services/cognitive-services/text-analytics/

Categories and Features

Categories and Features

Natural Language Processing

Co-Reference Resolution
In-Database Text Analytics
Named Entity Recognition
Natural Language Generation (NLG)
Open Source Integrations
Parsing
Part-of-Speech Tagging
Sentence Segmentation
Stemming/Lemmatization
Tokenization

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