Vanessa Lopez

Protecting vital public health programs with AI and Knowledge Graphs

A Talk by Vanessa Lopez (Research Scientist and Manager, AI for Health and Social Care, IBM Research - Ireland)

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About this Talk

Health and social services are complex domains that have a direct impact on people's lives and where vast amounts of money are spent globally.

When funding intended for public health programs is lost to Fraud Waste and Abuse, vulnerable citizens are ultimately the victims. In challenging times, ensuring financial integrity and fairer distribution of services by reducing disparities are among the top priorities for healthcare systems.

In this talk, I will provide a perspective from my journey in adopting research in Knowledge Graphs and AI to address significant societal problems in the healthcare industry.

In particular, Knowledge Graphs emerged as a unifying technology that facilitates bringing diverse data sources together to unlock new knowledge and empower professionals to reduce healthcare disparities.

Through a combination of natural language understanding, deep learning, and knowledge representation for modelling human-expertise and reasoning, we are investigating unique functionalities to automatically extract actionable knowledge from large text policy documents.

We identify medical claims that infringe policy, either intentionally (fraudulent) or unintentionally (e.g., providing unnecessary services or inconsistent with accepted medical practices).

We aim to understand the social program levers that drive positive health.

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02 December 2020, 12:20 PM

12:20 PM - 01:00 PM

About The Speaker

Vanessa Lopez

Vanessa Lopez

Research Scientist and Manager, AI for Health and Social Care, IBM Research - Ireland

Vanessa's research interests are to investigate and envision technologies to better understand human needs and support us, as a society, to target complex problems in the health and social care domain. In particular using a combination of semantic, natural language and learning technologies to capture, integrate, search and query diverse data, and apply it to solve real challenges, like for Integrated Care, to support the care of the most vulnerable citizens and to ultimately obtain better outcomes