Decision Support for Video-based Detection of Flu Symptoms

• URL: http://arxiv.org/abs/2008.10534v1
• Date: Mon, 24 Aug 2020 16:16:38 GMT
• Title: Decision Support for Video-based Detection of Flu Symptoms
• Authors: Kenneth Lai and Svetlana N. Yanushkevich
• Abstract summary: This paper addresses the capability of using results from a machine-learning model as evidence for a cognitive decision support system. We propose risk and trust measures as a metric to bridge between machine-learning and machine-reasoning.
• Score: 3.0255457622022486
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: The development of decision support systems is a growing domain that can be applied in the area of disease control and diagnostics. Using video-based surveillance data, skeleton features are extracted to perform action recognition, specifically the detection and recognition of coughing and sneezing motions. Providing evidence of flu-like symptoms, a decision support system based on causal networks is capable of providing the operator with vital information for decision-making. A modified residual temporal convolutional network is proposed for action recognition using skeleton features. This paper addresses the capability of using results from a machine-learning model as evidence for a cognitive decision support system. We propose risk and trust measures as a metric to bridge between machine-learning and machine-reasoning. We provide experiments on evaluating the performance of the proposed network and how these performance measures can be combined with risk to generate trust.

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