AICOM-MP: an AI-based Monkeypox Detector for Resource-Constrained Environments. (arXiv:2211.14313v1 [eess.IV])

Under the Autonomous Mobile Clinics (AMCs) initiative, we are developing,
open sourcing, and standardizing health AI technologies to enable healthcare
access in least developed countries (LDCs). We deem AMCs as the next generation
of health care delivery platforms, whereas health AI engines are applications
on these platforms, similar to how various applications expand the usage
scenarios of smart phones. Facing the recent global monkeypox outbreak, in this
article, we introduce AICOM-MP, an AI-based monkeypox detector specially aiming
for handling images taken from resource-constrained devices. Compared to
existing AI-based monkeypox detectors, 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. We have also open sourced both the
source code and the dataset of AICOM-MP to allow health AI professionals to
integrate AICOM-MP into their services. Also, through the AICOM-MP project, we
have generalized a methodology of developing health AI technologies for AMCs to
allow universal access even in resource-constrained environments.