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MalariaSafe Predictor

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MalariaSafe Predictor

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AgroCycleAI Oct. 23, 2025
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Challenge: Safety and ethics

Industries

Health and wellnessSustainability & Environment

Technologies

Blockchain & infrastructureData science & analyticsNarrow AI

Tags

AIDF rules

Description

AI-powered diagnostic platform enabling early malaria detection via mobile microscopy and local data learning. Each test result is securely recorded on blockchain, ensuring traceability, accuracy, and patient confidentiality. Designed for rural clinics with limited infrastructure, it reduces diagnostic time, improves treatment precision, and contributes to real-time malaria mapping for health authorities.

Detailed Idea

Alignment with DF goals (BGI, Platform growth, community)

Problem description

Malaria diagnosis in rural Africa remains slow and inaccurate due to poor lab access, manual testing errors, and lack of trusted medical records. Over 90% of global malaria cases occur in sub-Saharan Africa, yet most clinics operate offline without verified diagnostics or interoperable health data, increasing mortality and misreporting. A digital, privacy-secure solution is critical.

Proposed Solutions

Partner with local ministries and NGOs to deploy solar-powered diagnostic kits. Train community health officers to use mobile AI tools and ensure encrypted reporting to national malaria databases. Pilot in Nigeria’s endemic regions, measuring detection accuracy, reduced diagnostic delays, and integration with existing public health surveillance frameworks.

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