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What is Deep Lens VIPER?

VIPER enhances the screening process by automating the identification of remote patients at the diagnosis phase, thereby ensuring that qualified candidates are enrolled. Utilizing artificial intelligence, the system adeptly aligns patients with precision trials during a vital enrollment window, drawing on lab-agnostic genomic data, electronic medical records (EMR), and pathology data that cater to individual patient profiles and specific research demands. The specialized matching engine rigorously searches for the most appropriate clinical trials that correlate with a patient's diagnosis as soon as it is made. Moreover, VIPER integrates seamlessly into existing workflows, providing real-time notifications about patient eligibility for ongoing trials, which keeps the entire healthcare team informed during this critical period. In addition to these features, VIPER incorporates interactive dashboards that facilitate extensive data mining, enabling the collection and analysis of site and study-level patient information to effectively achieve study key performance indicators (KPIs). This holistic strategy not only boosts the efficiency of trial recruitment but also significantly aids researchers in reaching their objectives with greater success. By continuously refining its processes, VIPER stands to further revolutionize the landscape of clinical trial enrollment.

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

Deep Lens

Date Founded

2017

Company Location

United States

Company Website

www.deeplens.ai/deep-lens-healthcare-providers

Company Facts

Organization Name

Amazon

Date Founded

1994

Company Location

United States

Company Website

aws.amazon.com/comprehend/medical/

Categories and Features

Clinical Trial Management

21 CFR Part 11 Compliance
Document Management
Electronic Data Capture
Enrollment Management
HIPAA Compliant
Monitoring
Patient Database
Recruiting Management
Scheduling
Study Planning

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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