This repository contains data and code for the MassAITC AgeTech Researcher Knowledge Base web application. The knowledge base is designed to help identify AgeTech experts working on different health problems using different technologies. The knowledge base was generated by searching the OpenAlex research knowledge graph for AgeTech related research papers. We define AgeTech research papers to be papers that apply technology approaches to problems in aging. We identify AgeTech research papers by searching OpenAlex for papers that match specific combinations of keywords (for example, "computer vision and frailty"). The current knowledge base includes the 100 researchers with the most AgeTech papers indexed in OpenAlex.
The MassAITC AgeTech Researcher Knowledge Base app provides functions for browsing, searching and viewing information about AgeTech researchers included in the knowledge base. Researcher profiles were constructed using data from OpenAlex and OrcID. Profiles include research affiliations, top research topics, top co-authors within the knowledge base, and a listing of AgeTech papers with citation counts. In addition, each profile includes an AgeTech-specific generative AI research summary based on the researcher's five most recent papers and five most cited papers. Profiles include a visualization of each researcher's co-author graph within the knowledge base, and links to external profiles on OpenAlex and OrcID.
MassAITC AgeTech Researcher Knowledge Base web application can be accessed at https://reml-lab.github.io/agetech-researcher-kb/
