Risk history is scattered
Exposure, family history, symptoms, and previous screening often live across disconnected notes.
Explainable early cancer screening support
From patient history to timely referral.
O.A.S.I.S. helps frontline healthcare workers assess oral, breast, and cervical screening priorities using structured history, clinical safety rules, and explainable recommendations.
Clinical pathway engine
Structured assessment flow
OOral
BBreast
CCervical
HistoryRisk signalsSafety rulesRecommendation
- Explainable recommendations
- Red-flag safety overrides
- Screening workflow support
- Referral prioritisation
The care gap
Screening decisions are often delayed by fragmented information.
Red-flag symptoms can be overlooked
High-concern findings need to rise above routine scoring and eligibility checks every time.
Referral completion is difficult to track
The path from initial concern to examination, referral, and follow-up is rarely visible in one place.
The O.A.S.I.S. workflow
One structured workflow. Three cancer pathways.
Move from the patient encounter to a visible next action without hiding the clinical reasoning in a black box.
1
Capture patient history
2
Identify red flags
3
Check screening eligibility
4
Generate explainable priority
5
Prepare referral
6
Track follow-up
Pathway coverage
Focused support for three screening pathways.
Each pathway captures the risk factors, symptoms, and screening context that matter to its clinical workflow.
Oral screening
- tobacco and areca-nut exposure
- persistent lesions
- oral examination priority
Breast screening
- symptoms
- personal and family history
- clinical examination eligibility
Cervical screening
- previous screening
- abnormal results
- symptom and follow-up priority
Safety-first architecture
Clinical warning signs always come first.
A low model output never suppresses a concerning symptom or abnormal examination finding.
Decision hierarchy
Routine guidance
Screening priority
Prompt Referral
Final recommendation = highest urgency of
Red flags + Screening eligibility + Statistical support
Explainability built in
See the recommendation and the reasons behind it.
Every priority is traceable to the patient information that produced it, so clinicians can review the recommendation in context.
Oral pathway
Prompt Referral
Screening Priority Index
95/100
Why
- Persistent white oral patch
- Long-term smokeless tobacco exposure
- Areca-nut exposure
- Screening overdue
Recommended action
Prompt clinical oral examination and referral.
This is a referral-priority recommendation, not a cancer diagnosis.
Workflow comparison
Replace uncertainty with a visible care pathway.
Before O.A.S.I.S.
- scattered notes
- subjective triage
- unclear referral priority
- no follow-up visibility
With O.A.S.I.S.
- structured assessment
- safety overrides
- explainable recommendation
- trackable referral
Research-backed direction
Designed around evidence, transparency, and extension.
Clinical decision support in oncology
Structured support that keeps clinical judgement and local pathways at the centre.
Machine-learning risk stratification
Statistical signals can support prioritisation without overriding clinical warning signs.
Explainable decision support
Outputs are paired with the specific findings that contributed to each recommendation.
Multimodal future extension
A research direction for responsibly combining structured data with additional clinical inputs.