natural language processing

Explainable Health Risk Predictor with Transformer-based Medicare Claim Encoder

In 2019, The Centers for Medicare and Medicaid Services (CMS) launched an Artificial Intelligence (AI) Health Outcomes Challenge seeking solutions to predict risk in value-based care for incorporation into CMS Innovation Center payment and service …

Narratives and Needs: Analyzing Experiences of Cyclone Amphan Using Twitter Discourse

People often turn to social media to comment upon and share information about major global events. Accordingly, social media is receiving increasing attention as a rich data source for understanding people's social, political and economic experiences …

Reg2Vec: A Spatial Mapping of Economic Regulation

In this study, we use word and document embedding techniques from natural language processing to contextualize policymaking in U.S. federal agencies. We specifically look at a range of agencies responsible for economic regulation and train a model …

Central Bank Communication and the Yield Curve: A Semi-Automatic Approach using Non-Negative Matrix Factorization

Communication is now a standard tool in the central bank's monetary policy toolkit. Theoretically, communication provides the central bank an opportunity to guide public expectations, and it has been shown empirically that central bank communication …

Amphan: Analyzing Experiences of Extreme Weather Events using Online Data

Data Science for Social Good, Solve for Good

Fed2Vec

Developing a word and document embedding model for speeches by the Federal Reserve

Natural Language Processing: An Application in Public Policy

Repository for PyCon Ireland 2018 session