Learning Platform
Cervical Cancer Learning Platform
Interactive, AI-enhanced training for cytologists and pathology professionals — build diagnostic confidence with real cases and instant feedback
Why Cytology Education Needs to Evolve
Cervical cancer remains a significant global health challenge, with over half a million new cases and more than 300,000 deaths each year. Ensuring that cytologists are well-trained, confident, and accurate in their diagnostic abilities is paramount — yet traditional training methods struggle to keep pace.
Limited Access to Quality Training Materials
Most cytology training relies on textbooks and limited slide sets. Trainees rarely encounter the full range of abnormalities they will face in practice, leaving gaps in their diagnostic vocabulary.
Scarcity of Expert-Annotated Samples
High-quality, expert-verified cell annotations are difficult and expensive to produce. Without them, trainees lack the gold-standard reference points needed to calibrate their judgement.
No Objective Feedback Loop
Traditional training offers no way to measure diagnostic accuracy over time. Cytologists complete cases without knowing how their assessments compare to expert consensus.
Inconsistent Training Quality Worldwide
Access to experienced mentors and well-equipped training labs varies dramatically between institutions and countries, creating uneven standards of care.
What the Platform Offers
Everything cytologists need to learn, practise, and validate their diagnostic skills
A comprehensive library of fully diagnosed cervical smear samples spanning normal, ASCUS, LSIL, HSIL, SCC, and other Bethesda categories — each verified by experienced pathologists.
Detailed, cell-level annotations highlighting subtle morphological changes and rare cytological findings, empowering learners to recognise early-stage abnormalities and nuanced patterns.
In-depth video courses covering fundamental cytopathology concepts, advanced diagnostic techniques, and emerging best practices in cervical cancer screening.
Leveraging the same algorithms that power ScanAI, the platform provides real-time feedback on your diagnostic decisions — highlighting where your assessment aligns with or diverges from the AI and expert consensus.
Take timed diagnostic tests on randomised slide sets, then review detailed results comparing your predictions against the correct diagnoses to pinpoint strengths and areas for improvement.
Practise using the same scan viewer, AI annotations, confidence filters, and diagnostic submission workflow used in clinical ScanAI — so the transition from learning to real-world diagnosis is seamless.
How the Test Mode Works
The Learning Platform includes a structured test mode designed to simulate real diagnostic workflows. It gives you objective, measurable feedback on your performance — something traditional training cannot provide.
Start Test Mode
Click "Start Test Mode" to receive a randomised set of slides. Navigate each slide using the full ScanAI toolset — zoom, adjust contrast, filter annotations by cell type and confidence.
Submit Your Diagnosis
For each slide, select your diagnosis from the Bethesda categories, note any microorganisms or sample properties, and add free-text comments — just as you would in a clinical setting.
Review Your Results
After completing a test, view a side-by-side comparison of your predictions against the expert diagnoses. Identify patterns in your accuracy across different categories.
Track Progress Over Time
Repeat tests to measure improvement. The platform records your history so you can see how your diagnostic confidence and accuracy evolve with practice.
Built on the ScanAI Platform
The Learning Platform runs inside the same interface used for clinical diagnosis on ScanAI. Every tool, shortcut, and workflow you learn here translates directly to real-world use — no re-training needed when you move to production.
Scan Viewer with Zoom & Image Controls
Explore whole-slide images at any magnification. Adjust brightness, contrast, and gamma for optimal clarity. Navigate with keyboard shortcuts, mouse, or the minimap.
AI Annotations with Confidence Scores
Every cell is evaluated by ScanAI and assigned a probability of dysplasia. Filter annotations by confidence threshold or Bethesda category to focus on what matters.
Cell-Level Detail on Hover
Hover over any flagged cell to see its predicted type, confidence score, dimensions in microns, and any user comments — all the context you need in one tooltip.
Approve, Reject & Comment
Interact with each AI prediction: approve or reject the classification, add notes, and edit cell types. In learning mode these changes are non-destructive, so you can experiment freely.
Sample Training Video
Watch a sample from our video lecture series covering cervical cytological abnormalities — Cytological Features of LSIL.
Who Is This For?
The platform serves professionals at every stage of their career
Build foundational skills with expert-verified slides and structured test modes. Get objective feedback from day one — no need to wait for a mentor review.
Sharpen your eye on rare and borderline cases. Use the platform for continuing education, proficiency testing, or as a second-opinion reference library.
Standardise your curriculum with a consistent, globally accessible training environment. Track student progress and benchmark performance across cohorts.
Start Learning Today
Sign up for the Cervical Cancer Learning Platform — it's free for individual learners. Institutions interested in group licences or curriculum integration can contact us directly.