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What is Imagia EVIDENS?

EVIDENS is a cutting-edge AI platform designed to streamline the identification of digital cohorts, enhancing research capabilities and fostering collaboration while allowing insights to be shared across vast hospital data sets. Users can quickly annotate and transform data into formats compatible with AI, enabling them to filter populations based on diverse clinical outcomes or demographic characteristics efficiently. The platform supports extensive keyword filtering, empowering users to train AI models for precise searches. In addition, intelligent AI tools assist users in exploring and setting criteria for identifying cohorts. The automation of the analysis process through AI model training allows for the rapid categorization of data into well-defined groups. EVIDENS produces AI-ready cohorts that facilitate the testing of clinical hypotheses in various research studies. Users can easily track the progress and tasks of all their projects and collaborators, as well as engage with activities related to their specific research interests. Furthermore, the platform includes collaborative tools that encourage simultaneous efforts in the creation, training, and validation of AI models, thereby nurturing a thriving research environment. Overall, EVIDENS not only simplifies the research process but also enhances the effectiveness and efficiency of all participants involved, making it a pivotal tool in contemporary research settings. By leveraging such advanced capabilities, researchers can unlock new possibilities in understanding complex medical data.

What is Clinical Extract?

Clinical Extract can efficiently obtain research data from any electronic health record system that utilizes a certified bulk FHIR API, including well-known platforms such as Epic, Oracle Health (Cerner), athenahealth, eClinicalWorks, MEDITECH, NextGen, and Veradigm. The tool functions as a SMART Backend Services client within your existing infrastructure, employing read-only permissions and enabling the export of only the specified study group through a Group $export. It converts NDJSON into a detailed CSV format, complete with a data dictionary that correlates each column to its corresponding FHIR element, all while ensuring that patient data stays securely within your environment. Tailored specifically for cancer and clinical registries, it supports coded case and abstraction fields in line with the NAACCR layout and addresses the requirements of research informatics teams and ethical brokers by providing study-specific data collections alongside an IRB-compliant data dictionary. Additionally, it aids research sites in evaluating clinical trial feasibility based on established coded criteria. Among its key capabilities are a cohort builder, roster extraction using FHIR $match, and the creation of both the CSV and data dictionary, plus a specialized oncology perspective that highlights biomarkers and TNM stage as distinctly labeled columns for straightforward analysis. This holistic method significantly improves the accessibility and applicability of essential health data for a variety of research initiatives, thereby streamlining the overall research process. Ultimately, Clinical Extract serves as a vital resource for enhancing the efficiency and effectiveness of health data research.

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Media

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Integrations Supported

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Integrations Supported

Additional information not provided

API Availability

API Availability

Pricing Information

Pricing not provided

Pricing Information

Pricing not provided

Supported Platforms

SaaS

Supported Platforms

On-Prem
Linux

Customer Service / Support

Standard Support
Web-Based Support

Customer Service / Support

Web-Based Support

Training Options

Not specified

Training Options

Documentation Hub

Company Facts

Organization Name

Imagia

Date Founded

2015

Company Location

Canada

Company Website

imagia.com/our-platform/

Company Facts

Organization Name

Saga IT

Date Founded

2016

Company Location

United States

Company Website

clinicalextract.com

Categories and Features

Healthcare

Not specified

Healthcare AI

Not specified

Categories and Features

Healthcare Analytics

Not specified

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