Toward Next Generation Integrative Semantic Health Information Assistants

Managing a complex illness often requires different treatment regimens spread over a long time. The complexity of these potentially life-threatening diagnoses can be daunting to patients while they are most vulnerable. We present a vision for artificial intelligence-enabled tools for assisting patients in managing the complex information given to them over the course of their treatments through the combination of existing and emerging techniques from natural language processing and knowledge representation. We provide examples from an actual breast cancer diagnosis and treatment plan and highlight the development of new combinations of techniques to build tools that can reason about data from a variety of sources and act as intelligence-augmenting agents. We conclude with a discussion of some additional challenges facing artificial intelligence practitioners as applications become patient-centric.


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We aim to find new effective treatments for disease using existing drugs. Our approach is to gather and integrate existing data using semantic technologies to help discover promising drug repurposing.

Many diseases are based on genetic or epigenetic changes that can be targeted indirectly via upstream regulatory pathways. Targets need to have a high likelihood of affecting all possible changes, and so need to have upstream interactions that cover multiple genotypes/epigenotypes that might drive the same phenotype.

Sensor-based health monitors are increasing in usage and are providing growing amounts of data about our health and daily activities. These monitors are increasingly included in or integrated with mobile devices.

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