Automatic Mapping of Terminology Items with Transformers
- Alberto Purpura
- Joao Bettencourt-Silva
- et al.
- 2023
- AMIA Annual Symposium 2023
Joao is a Senior Research Scientist and Strategy Coordinator in Healthcare & Lifesciences at IBM Research. Joao's most recent published research works are available in his Google Scholar Profile (Dr Joao H. Bettencourt-Silva, PhD, FAMIA).
Prior to joining IBM Joao was a Postdoctoral Research Fellow in Clinical Informatics at Cambridge University, UK where he continued to maintain a honorary fellowship to work in research projects using Electronic (Bio)Medical Records for research and service improvement. Joao has over 10 years experience working in the UK National Health Service (NHS) in various capacities, from data analysis and auditing, management and clinical research. In 2024, Joao was awarded the American Medical Informatics Association Fellowship (FAMIA).
His doctoral research project focused on the development of novel computational methods and techniques to reuse routine clinical data from multiple sources for research, service improvement and decision support. Joao has designed and delivered clinical data warehouses, data models and software to extract, organise, synthesise and analyse complex clinical information, and carried out various analyses and clinical research projects using linked health data. He has experience in electronic medical record (EMR) implementations in the NHS and developed methodologies, protocols and electronic infrastructures to facilitate the interface between computers, clinicians and researchers. In particular, Joao has researched methods for modelling and visualising the journeys that patients take through care based on multiple heterogeneous data sources.
His research interests include artificial intelligence, biomedical foundation models, AI for scientific discovery, agentic workflows, the reuse of multimodal and heterogeneous data for research (e.g., biomedical, clinical, and social determinants), visualisation and modelling of complex biomedical and health information, NLP, data and process mining and machine learning applications in health and biomedical sciences.