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Deep Learning: Current and Emerging Applications in Medicine and Technology

机译:深度学习:医学和技术中的当前和新兴应用

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Machine learning is enabling researchers to analyze and understand increasingly complex physical and biological phenomena in traditional fields such as biology, medicine, and engineering and emerging fields like synthetic biology, automated chemical synthesis, and biomanufacturing. These fields require new paradigms toward understanding increasingly complex data and converting such data into medical products and services for patients. The move toward deep learning and complex modeling is an attempt to bridge the gap between acquiring massive quantities of complex data, and converting such data into practical insights. Here, we provide an overview of the field of machine learning, its current applications and needs in traditional and emerging fields, and discuss an illustrative attempt at using deep learning to understand swarm behavior of molecular shuttles.
机译:机器学习使研究人员能够分析和理解生物学,医学和工程学等传统领域和合成生物学,自动化化学合成和生物制造等新兴领域中日益复杂的物理和生物学现象。这些领域需要新的范式,以理解日益复杂的数据并将此类数据转换为患者的医疗产品和服务。迈向深度学习和复杂建模的尝试是弥合获取大量复杂数据并将这些数据转换为实际见解之间的鸿沟。在这里,我们提供了机器学习领域的概述,它在传统领域和新兴领域中的当前应用和需求,并讨论了使用深度学习理解分子穿梭机群行为的说明性尝试。

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