The foundation is calling on data scientists, software engineers, designers, and researchers to build an open-source software application that brings advances from machine learning to practicing clinicians. The goal of the challenge is to bridge the gap between research algorithms and clinical practice in early detection by developing an end-to-end application that connects the predictive power of machine learning with functional software tested against errors and a clean user interface focused on clinical use, according to the foundation.
The project needs data scientists to build the machine-learning algorithms, software engineers to develop back-end functions and data pipelines, engineers and designers to build out the user interface, and community contributions to enrich the documentation, discussions, and outreach, according to the foundation. Top contributors will be eligible for a share of $100,000 in prize money.
The challenge will be run by DrivenData, which holds online machine-learning competitions. More information on the challenge can be found here.
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