Rad AI
Revolutionizing radiology with AI-driven efficiency and accuracy enhancements.. [Contact for Pricing]
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What is Rad AI?
Rad AI is a generative AI platform built specifically for radiology workflows, created by radiologists to save time, reduce burnout, and improve patient care. The company offers three main products: Rad AI Reporting (a comprehensive radiology reporting software), Rad AI Impressions (automated impression generation), and Rad AI Continuity (automated patient follow-up management for incidental findings).
Rad AI Reporting uses advanced machine learning and generative AI to convert dictated findings into structured, standardized reports. It reduces dictation time by up to 50% and words dictated by up to 90%. Rad AI Impressions automatically generates report impressions customized to each radiologist's language and style in 0.5 to 3 seconds, saving radiologists 60+ minutes per shift. Rad AI Continuity tracks more than 50 categories of incidental findings and automates communication with providers and patients, doubling follow-up rates for significant actionable findings.
The platform is designed for radiologists, radiology practices, health systems, and IT teams. It works with over 40% of all US health systems and 9 of the 10 largest US radiology practices. The software integrates seamlessly with existing PACS, RIS, and EHR systems via HL7/FHIR/FHIRcast standards, supports existing templates and microphones, and requires zero workflow changes.
Key features include zero-click automation, consensus guideline recommendations (Fleischner, Incidental Thyroid Nodules, AAA), SOC 2 Type II and HIPAA+ certification, cloud-native deployment with no servers needed, and the ability to catch clinically significant errors in 5% of reports. The platform uses proprietary generative AI models trained on half a billion radiology reports.
Rad AI pricing
Pricing model: Freemium
Rad AI uses enterprise/custom pricing with no public pricing details available on their website. The company does not offer a free tier or free plan. Pricing is custom-quoted based on practice size and needs. There is no free trial available. The platform serves over 40% of US health systems and 9 of the 10 largest US radiology practices, indicating enterprise-level deployment. Customers must request a demo to get pricing information.
Rad AI pros
- Saves 60+ minutes per shift for radiologists
- Reduces words dictated by up to 35-90%
- 84% of radiologists report reduced burnout
- Impressions generated in 0.5 to 3 seconds
- Zero-click automation with no workflow changes
- Customizes impression language to each radiologist
- Automatically inserts consensus guideline recommendations
- Catches clinically significant errors in 5% of reports
- Integrates with existing PACS/RIS/EHR via HL7/FHIR
- Cloud-native deployment with no servers or VMs needed
- SOC 2 Type II and HIPAA+ certified security
- Tracks 50+ categories of incidental findings
- Doubles patient follow-up rates for actionable findings
- Increases clinically appropriate follow-ups by up to 40%
- Supports all specialties and modalities
- Lightweight client with SSO and optional auto-update
- Works with existing templates, microphones, and hardware
- Trained on one of the largest proprietary radiology datasets
- Improved report accuracy and standardization
- Reduces liability for health systems and practices
Rad AI cons
- Enterprise pricing only, no public pricing available
- No free tier or freemium option offered
- Requires internet access for cloud deployment
- XML/JSON file integrations only work with desktop app, not web version
- FHIRcast topic is lost if desktop app is closed and reopened
- Primarily focused on US health systems, limited international presence
- Deep learning requires proprietary radiology report dataset access
- May require practice adaptation to AI-generated impressions initially
Frequently asked questions about Rad AI
What is Rad AI Reporting?
Rad AI Reporting is a breakthrough radiology AI reporting platform built on generative AI that boosts productivity while minimizing fatigue. It employs advanced machine learning algorithms and generative AI to create comprehensive and accurate reports with remarkable speed. Users dictate findings using their existing microphone, PACS, RIS, and EHR systems, and the AI generates structured reports. It reduces dictation times by up to 50% and words dictated by up to 90%.
How does Rad AI Impressions work?
Rad AI Impressions automatically generates report impressions from dictated findings, with language individually customized to each radiologist and practice. Users dictate their study indication and findings using preferred VR software, and the AI auto-generates the impression in 0.5 to 3 seconds using their preferred language and style. The radiologist then reviews and approves the final report. It saves radiologists 60+ minutes per shift and reduces words dictated by up to 35%.
What is Rad AI Continuity?
Rad AI Continuity is an AI-driven patient follow-up management platform that closes the loop on follow-up recommendations for significant incidental findings in radiology reports. It identifies and categorizes follow-up recommendations using proprietary AI models trained on half a billion reports, automates communication with providers and patients via SMS, direct mail, and EHR messaging, and automatically closes the loop on follow-up. It tracks 50+ categories of incidental findings and can double follow-up rates.
How does Rad AI customize reports for each radiologist?
Rad AI uses proprietary generative AI models trained specifically for radiology and healthcare, along with one of the largest proprietary radiology report datasets in the world. The AI learns each radiologist's preferred language and dictation style, then generates impressions that match their individual voice. This customization happens automatically without requiring radiologists to change their workflow or training.
How secure is Rad AI's system?
Rad AI is SOC 2 Type II and HIPAA+ certified with state-of-the-art monitoring performing over 130 tests daily. The platform features an industry-leading de-identification pipeline specialized to radiology reports, robust encryption, and access controls. It prioritizes high-level security and compliance standards to ensure patient data is protected. The cloud-native architecture requires no servers or VMs to be set up by IT teams.
How does Rad AI improve diagnostic accuracy?
Rad AI helps catch and fix clinically significant errors in 5% of all reports through its AI Omni feature. It automatically inserts consensus guideline recommendations (such as Fleischner, Incidental Thyroid Nodules, AAA) so radiologists don't need to search for white papers or scroll through macros. The AI pulls down significant incidental findings that should be mentioned and ensures impressions answer the ordering clinician's main question, improving overall report accuracy and standardization.
What integrations does Rad AI support?
Rad AI seamlessly integrates with existing PACS, RIS, and EHR systems via HL7/FHIR/FHIRcast standards. It supports XML and JSON file integrations for data synchronization between Rad AI Reporting and external systems. The platform is an open platform for AI with standards-based architecture that allows integrations from all AI vendors. It supports OIDM and HL7 FHIR standards, enabling simple API integration for IT administrators.
How does Rad AI impact radiologist workflow?
Rad AI requires zero-click automation with zero change to existing workflow. Radiologists use their preferred VR software, existing templates, microphones, and computers. Impressions populate in 0.5 to 3 seconds after dictating findings. The AI provides a cognitive break between reports while allowing radiologists to keep their eyes on images. It reduces repetitive administrative tasks and mental strain from summarizing findings, enabling radiologists to achieve a flow state with less perceived effort.
Who founded Rad AI and what is their background?
Rad AI was founded in 2018 by Dr. Jeff Chang (Co-founder and CPO) and Doktor Gurson (Co-founder and CEO). Dr. Jeff Chang is one of America's best-known radiologists and the youngest US radiologist in history, who started medical school at NYU at age 16, completed a fellowship in musculoskeletal MRI, and worked overnights as an ER radiologist for 10 years. He pursued graduate work in machine learning with deep learning specialization. Doktor Gurson is a serial tech entrepreneur who started at age 16 and has a 20-year tech career with multiple startups and acquisitions.
What consensus guidelines does Rad AI automatically insert?
Rad AI automatically inserts consensus guideline recommendations including Fleischner guidelines for incidental pulmonary nodules, Incidental Thyroid Nodules guidelines, AAA (abdominal aortic aneurysm) guidelines, and many others. The AI pulls appropriate follow-up recommendations based on nationally accepted consensus guidelines, eliminating the need for radiologists to search white papers or scroll through macros to find the right recommendations for their reports.