Point-of-Care Ultrasound (PoCUS) is a powerfully versatile and virtually consumable-free clinical tool for the diagnosis and management of a range of diseases. Recent ultrasound-on-a-chip technology has transformed the expensive, fragile and cumbersome 20kg ultrasound trolley into a robust, pocket-sized, portable tool, pluggable into a smart phone and costing a 10th of the price with most of the same functionalities.
While the promise of this tool in resource-limited settings may seem obvious, it’s implementation is limited by inter-user bias, requiring specific training and standardisation.
This makes PoCUS a good candidate for computer-aided interpretation support.
Our study proposes the development of a PoCUS training program adapted to resource limited settings and the particular needs of the ICRC. We encourage locally led research and build a databank to create deep learning algorithms that support the standardisation of clinical ultrasound interpretation.