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.
翻译:根据自主移动诊所(AMCs)倡议,我们正在开发、开源和标准化健康AI技术,使最不发达国家能够获得医疗保健。我们认为AMCs是下一代保健提供平台,而健康AI引擎则是这些平台上的应用,类似于各种应用如何扩大智能电话的使用情景。面对最近的全球天花爆发,我们在文章中引入了AICOM-MP,这是一个AICOM-MP,专门用来处理来自资源受限制装置的图像的AI-MP检测器。与现有的基于AI的猴子天花探测器相比,AICOM-MP已经取得了最先进的性能。我们已经将AICOM-MP作为网络服务,允许普遍使用猴子天花筛查技术。我们还开通了源代码和AICOM-MP数据集,以使卫生AI的专业人员能够将AICOM-MP纳入其服务。此外,通过AICOM-MP项目,我们推广了为AMs开发健康AI技术的方法,以便即使在资源受限制的环境中也能普遍使用。