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What is Tempus?

Tempus AI, a leading health tech company located in Chicago, Illinois, is focused on revolutionizing patient care through the integration of advanced artificial intelligence and precision medicine. By harnessing data and AI, the firm aims to develop customized treatment strategies spanning various medical fields, including oncology, cardiology, radiology, and mental health. Their comprehensive platform merges genomic sequencing, clinical data, and AI-driven analytics, thereby providing healthcare professionals and researchers with vital insights. Tempus enhances patient understanding through a variety of testing methodologies, such as tissue and liquid biopsies, DNA and RNA sequencing, somatic and germline testing, as well as tumor-normal matched profiling and minimal residual disease monitoring. In addition, the company presents a fast and reliable platform for test ordering, acquiring patient insights, and integrating AI technologies into medical practice. Their innovative generative AI-enabled clinical assistant further streamlines access to patient insights, improving the efficiency of healthcare delivery. This dedication to leveraging state-of-the-art technology underscores Tempus AI's mission to elevate health outcomes and propel advancements in medical research. Ultimately, Tempus AI strives to be at the forefront of a transformative era in healthcare.

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

AWS AI Services
AWS App Mesh
Amazon Comprehend

Integrations Supported

AWS AI Services
AWS App Mesh
Amazon Comprehend

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

Tempus

Date Founded

2015

Company Location

United States

Company Website

www.tempus.com

Company Facts

Organization Name

Amazon

Date Founded

1994

Company Location

United States

Company Website

aws.amazon.com/comprehend/medical/

Categories and Features

Categories and Features

Data Extraction

Disparate Data Collection
Document Extraction
Email Address Extraction
IP Address Extraction
Image Extraction
Phone Number Extraction
Pricing Extraction
Web Data Extraction

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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