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Abstract Neuromorphic computing could be used to directly perform complex classification tasks in hardware and is of potential value in the development of wearable, implantable and point-of-care devices. Successful implementation requires low-power operation, simple sensor integration and straightforward training. Organic materials are possible building blocks for neuromorphic systems, offering low-voltage operation and excellent tunability.
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