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AI assisted diagnosis

AI powered solution that listens to patients’ symptoms and health concerns and offers diagnosis support to the clinician, thereby reducing errors and accelerating the diagnosis. Solution can be further expanded into additional areas of decision support.

Key Benefits

Increased accuracy

of diagnoses leveraging AI technology, improving medical outcomes

Improved efficiency

of medical care, through more efficient and accurate diagnoses

Enabled opportunities

to explore more areas where AI and machine learning can provide decision making support to hospitals and care providers

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User Journey

1
Abdulaziz goes to the hospital after an episode of chest pain Abdulaziz’s physician prescribes him a new medication
2
3
4
5

Potential Service Features

  • Diagnosis report
  • Automated reports
  • Patient file sharing
  • Electronic prescription
  • Insurance company synchronization
  • Predictive analytics

Implementation Analysis

IMPLEMENTATION TIMELINE

ShortMediumLong

TECHNOLOGY COMMERCIAL VIABILITY

Currently viableViable in Short TermViable in Long Term

REGULATORY CONDUCIVENESS

FavourableChallengingComplex

INVESTMENT REQUIREMENTS

SmallMediumLarge

Key Implementation Considerations

1

High competence in UI/UX, big data analytics, AI, biomedical and genetic analytics, and database building and management.

2

Research phase to identify existing APIs that can be built on, entities with useful data and enablers for use case development, and a concept design phase to develop a comprehensive PoC

3

To be developed and scaled across all hospitals and clinics

4

UX/UI and medical score testing through focus groups to ensure rapid adoption and precise medical results.

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