Advanced techniques in machine learning combined with scalable "cloud" computing infrastructure are driving the creation of new and innovative health diagnostic applications. We describe a service and application for performing image training and recognition, tailored to dermatology and melanoma identification. The system implements new machine learning approaches to provide a feedback-driven training loop. This training sequence enhances classification performance by incrementally retraining the classifier model from expert responses. To easily provide this application and associated web service to clinical practices, we also describe a scalable cloud infrastructure, deployable in public cloud infrastructure and private, on-premise systems.
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Article Synopsis
- The report discusses the low adoption of robotic mitral repair procedures and outlines the authors' early experiences in successfully launching such a program.
- The strategy involved educating the team, hands-on practice, gradual progression, and careful patient selection, along with regular analysis and feedback.
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