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Augmenting Clinical Intelligence with Federated Learning, Imaging Analytics and Outcomes Decision Support
Augmenting Clinical Intelligence with Federated Learning, Imaging Analytics and Outcomes Decision Support
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机译:通过联合学习,成像分析和结果决策支持增强临床情报
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摘要
The invention integrates emerging applications, tools and techniques for machine learning in medicine with videoconference networking technology in novel business methods that support rapid adaptive learning for medical minds and machines. These methods can leverage domain knowledge and clinical expertise with networked cognitive collaboration, augmented clinical intelligence and cybernetic workflow streams for learning health care systems. The invention enables multimodal clinical communications, collaboration, consultation and instruction between and among heterogeneous networked teams of persons, machines, devices, neural networks, robots and algorithms. It provides for both synchronous and asynchronous cognitive collaboration with multichannel, multiplexed imagery data streams during various stages of medical disease and injury management—detection, diagnosis, prognosis, treatment, measurement, monitoring and reporting, as well as workflow optimization with operational analytics for outcomes, performance, results, resource utilization, resource consumption and costs. The invention enables cognitively-enriched, annotation and tagging, as well as encapsulation, saving and sharing of collaborated imagery data streams as packetized clinical intelligence.
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