AICOM-MP: an AI-based monkeypox detector for resource-constrained environments

Abstract

Under the Autonomous Mobile Clinics (AMCs) initiative, the AI Clinics on Mobile (AICOM) project is developing, open sourcing, and standardising health AI technologies on low-end mobile devices to enable health-care access in least-developed countries (LDCs). As the first step, we introduce AICOM-MP, an AI-based monkeypox detector specially aiming for handling images taken from resource-constrained devices. We have developed AICOM-MP with the following principles: minimisation of gender, racial, and age bias; ability to conduct binary classification without over-relying on computing power; capacity to produce accurate results irrespective of images' background, resolution, and quality. AICOM-MP has achieved state-of-the-art (SOTA) performance. We have hosted AICOM-MP as a web service to allow universal access to monkeypox screening technology, and open-sourced both the source code and the dataset of AICOM-MP to allow health AI professionals to integrate AICOM-MP into their services.