论文标题
AICOM-MP:基于AI的Monkeypox检测器,用于资源受限的环境
AICOM-MP: an AI-based Monkeypox Detector for Resource-Constrained Environments
论文作者
论文摘要
在自主移动诊所(AMCS)倡议下,我们正在开发,开放采购和标准化健康AI技术,以使最不发达国家(LDC)的医疗保健获得。我们认为AMC是下一代医疗保健提供平台,而健康AI发动机则是这些平台上的应用,类似于各种应用程序如何扩展智能手机的使用情况。面对最近的全球Monkeypox爆发,在本文中,我们介绍了AICOM-MP,这是一种基于AI的Monkeypox检测器,专门针对从资源受限设备拍摄的图像。与现有的基于AI的Monkeypox探测器相比,AICOM-MP达到了最先进的(SOTA)性能。我们已经托管了AICOM-MP作为Web服务,以允许通用Monkeypox筛选技术。我们还开放了AICOM-MP的源代码和数据集,以使健康AI专业人员能够将AICOM-MP集成到他们的服务中。此外,通过AICOM-MP项目,我们概括了一种为AMC开发健康AI技术的方法,即使在资源受限的环境中也可以通用访问。
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.