Intelligent Medical Platform for Clinical Decision Making
The objective of this research is to extend the core technologies of exiting clinical decision support systems (CDSS) infrastructure towards multi-level maintenance of knowledge bases by designing and developing innovative methods of knowledge acquisitions. The new idea is to design and develop evidence and dialogue based clinical decision support system to support diverse knowledge resources (i.e. unstructured text, images, and structured EMR/EHR data) for evolutionary knowledge base with novel technology. We propose dialogue-based Intelligent Medical Platform (IMP) that is a platform to support services on top of the incremental learning based on evolutionary knowledge bases from diverse sources by
integrating legacy systems with multiple data formats, supported by clinical standard-inspired big data persistence. The system is fitted out with dialogue environment in the form of text, voice, and image to physicians and patients during treatment, diagnosis and health related recommendations, alerts, coaching, and education. It overcomes the existing systems limitations in terms of evolutionary knowledge base, dialoging ability of interaction, integration with legacy healthcare systems such as hospital information and management systems (HMIS), and handling multimodal data from diverse input sources.
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