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Rad AI

Empowering physicians with best-in-class AI radiology solutions to save time, reduce burnout, and improve patient care.

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Description

Rad AI provides advanced AI-powered tools specifically designed for the field of radiology. Its solutions aim to streamline clinical workflows, significantly reducing the time radiologists spend on report dictation and impression generation. By automating key parts of the reporting process, Rad AI helps alleviate fatigue and burnout among physicians.

The platform includes features for automatically generating customized report impressions based on dictated findings and a system for managing follow-up recommendations for incidental findings. This ensures better continuity of care, helps close communication loops within healthcare systems, reduces potential liability, and ultimately contributes to improved patient safety and outcomes. The tools are designed for seamless integration into existing radiology workflows.

Key Features

  • Rad AI Reporting: Generative AI reporting platform boosting productivity and minimizing fatigue.
  • Rad AI Impressions: Automates radiology impression generation, saving 60+ minutes per shift and reducing burnout.
  • Rad AI Continuity: Automates patient follow-up management for significant incidental findings across 50+ categories.
  • Customized Language: Generates impressions tailored to each radiologist's specific language.
  • Workflow Integration: Offers zero-click automation for seamless integration without changing existing workflows.
  • Efficiency Improvement: Significantly reduces words dictated and saves time.
  • Burnout Reduction: Designed to decrease radiologist fatigue and stress.
  • Security Compliance: SOC 2 Type II and HIPAA+ certified with robust data de-identification.

Use Cases

  • Automating the generation of radiology report impressions.
  • Streamlining the creation of comprehensive radiology reports.
  • Managing and automating follow-up recommendations for incidental findings.
  • Reducing radiologist workload, fatigue, and burnout.
  • Improving the efficiency and accuracy of radiology reporting.
  • Enhancing patient safety and outcomes through reliable follow-up tracking.
  • Minimizing health system liability related to missed incidental findings.
  • Improving overall radiology department workflow efficiency.

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