Medicai's Radiology AI Co-Pilot turns a radiologist's dictation into a structured report draft, right inside the DICOM viewer. Dictate your findings, choose a template, and the AI organizes your words into report sections and drafts an impression. You review, edit, and sign.
Much of a radiologist's day goes to documentation rather than interpretation. The Radiology AI Co-Pilot takes on the repetitive writing work: transcribing dictation, organizing it into structured notes and report drafts, summarizing clinical information, and preparing documents for filing.
Medicai integrates with leading large language model services, including Azure OpenAI Service, OpenAI models, and Meta's Llama models.
The result is a faster path from dictation to a finished report, with the radiologist's findings and judgment unchanged.
The Co-Pilot converts unstructured dictation and clinical conversations into structured notes and report drafts, ready for the radiologist to review.
The Co-Pilot works inside the Medicai DICOM viewer, so radiologists draft reports alongside the images without switching applications.
Choose from a library of report templates, including your own user templates and templates in other languages, so drafts follow your practice's format. Pair it with Medicai's structured reporting for consistent, searchable reports.
The Co-Pilot runs within Medicai's platform, which is built to support HIPAA and GDPR requirements and operates under ISO 27001 information security certification.
The Co-Pilot sorts your dictated findings into the right sections of the selected template, such as history, technique, comparison, and findings by anatomical region.
Draft the impression from your own findings with one step, then edit it as needed.
Text placed by the AI appears in brackets, so you can see exactly what the Co-Pilot added. Review it, edit it, and remove the brackets when you are satisfied.
Run a proofreading pass to catch errors before you sign.
Share finished reports, generate a report QR code, or create a de-identified version of a report for teaching or research.
Every AI-generated draft is reviewed, edited, and signed by a radiologist before it becomes part of the record.
Use the chat panel to ask questions about the report you are writing.
AI-assisted reporting reduces the time radiologists spend writing, so more of their day goes to reading studies.
Mapping dictation into templates and drafting impressions reduces the typing and formatting that slow down reporting.
When drafting takes less time, finished reports can reach referring clinicians sooner.
Templates and structured sections help reports follow a consistent format across radiologists and sites.
Handing repetitive writing to the Co-Pilot leaves more of the radiologist's time for the images.
Employing state-of-the-art AI in healthcare, Medicai's Radiology AI Co-Pilot analyzes radiology images and supports clinicians in creating detailed medical reports. This approach augments the precision of clinical documentation and elevates the standards of patient care across various healthcare systems.
Our process begins with a thorough understanding of clinical needs. We analyze the specific requirements of radiology professionals, such as accurate diagnostics, workflow efficiency, and personalized reporting.
We then adjust the "Precision Parameters," such as "temperature" and "top_p," to balance creativity with factual consistency in the AI Co-Pilot's outputs.
The AI Co-Pilot is then released to assist radiology professionals with generating tailored, accurate reports. The generated content undergoes rigorous testing to ensure that it meets clinical standards and addresses the specific needs identified earlier.
Give it a try, play with it! Using our embeddable DICOM Viewer, you can easily view your DICOM files anywhere online (web, in the mobile application). Your DICOM files are stored in your Medicai workspace, in your cloud PACS.
"With Medicai's intuitive platform, I can seamlessly share cases, annotate images, and facilitate discussions, enhancing learning and collaboration within our community. It's truly a game-changer in advancing radiology education."
Sorin Ghiea
Medicai's Radiology AI Co-Pilot helps practices reduce documentation time and produce consistent reports, while every report remains the radiologist's work. For practices looking to ease reporting workload without changing who makes the clinical decisions, the Co-Pilot fits into the viewer and templates your team already uses.
What does Medicai's Radiology AI Co-Pilot do?
It turns a radiologist's dictation into a structured report draft inside the Medicai DICOM viewer. It maps dictated findings into the selected template, drafts the impression, and supports proofreading, sharing, and de-identification. Radiologists review, edit, and sign every report.
Does the AI Co-Pilot read the images or diagnose?
No. The Co-Pilot works only from the radiologist's dictated words. It does not analyze images to detect, prioritize, or diagnose findings. Interpretation remains the radiologist's responsibility.
How can I tell which text the AI wrote?
Text placed by the AI appears in brackets. The radiologist reviews and edits it, then removes the brackets before signing.
Can I use my own report templates?
Yes. The Co-Pilot works with a template library that includes user templates and templates in other languages, so drafts follow your practice's format.
Who is responsible for the final report?
The radiologist. The report is a draft until the radiologist signs it, and signing is a separate step.
Which AI models does the Co-Pilot use?
Medicai integrates with large language model services including Azure OpenAI Service, OpenAI models, and Meta's Llama models.
Is patient data protected?
The Co-Pilot runs within Medicai's platform, which is built to support HIPAA and GDPR requirements and is ISO 27001 certified.
How does the Co-Pilot fit with structured reporting?
The Co-Pilot can work within Medicai's structured reporting templates, so drafts follow your practice's format and produce consistent, searchable reports.
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