Rizin
Freemium
Users seeking adaptive, non-fixed workout programming
You get your knee MRI results, the radiologist report is dense with clinical shorthand, and your appointment is two weeks out — that gap is exactly what Analyze My Knee is built for.
The tool accepts DICOM files or PDF reports, processes them through a panel of four AI models working in parallel, and returns a single plain-language explanation of findings. Raw scan files never leave the browser — only rendered images are transmitted when you explicitly trigger analysis, which removes the most common privacy concern patients raise before uploading medical files. The 3D viewer runs entirely client-side with no install required. Where it breaks: this is a single-shot explanation service, not a diagnostic system, and the output is explicitly positioned as preparation material for a doctor visit — not a substitute for one. Teams or developers looking to integrate this into a clinical workflow have no API to call.
Bottom line: Use this to walk into your orthopedist appointment knowing what 'grade II posterior horn signal' means — not to skip that appointment.
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Freemium
Users seeking adaptive, non-fixed workout programming
Freemium
General medication information seekers
Radiology reports are written for clinicians. When a patient receives one without context, the terminology is opaque and the wait for a follow-up appointment creates anxiety that plain-language explanation can reduce. Analyze My Knee takes a knee MRI or X-ray — either as a DICOM file or a PDF report — runs it through four AI models in parallel, and produces a single consolidated explanation covering findings relevant to conditions like ACL tears, meniscus injuries, osteoarthritis, and fourteen other named knee conditions. The workflow is three steps: upload, wait for the panel to cross-check its outputs, receive one readable report.
The privacy architecture is the most technically differentiated aspect of the product. The vendor states that raw scan files never leave the browser — only rendered images are sent for AI analysis, and only when the user initiates it. For patients who are reluctant to upload sensitive medical imaging to a cloud service, this local-first approach removes the barrier. The free 3D viewer operates entirely in the browser with no account creation or file upload required.
This tool fits one scenario well: a patient who has imaging results in hand, wants to understand them before speaking to a doctor, and wants that understanding to come from more than one model cross-checking itself. It does not fit clinical integration workflows — the vendor states no API is available. It does not replace diagnostic review — the page carries an explicit medical disclaimer. And it is scoped to knee imaging only, though the vendor operates parallel sites for ankle, shoulder, hip, spine, elbow, wrist, and dental imaging under separate domains.
Supported input formats include DICOM files and PDF reports. Analysis is one-shot per upload — there is no iterative refinement, no session memory, and no mechanism for a user to ask follow-up questions of the AI panel after the report is generated.
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