Google Grant
The aim is to develop a modularised active learning framework within the Google Cloud Platform that enables the annotation of medical image data on a large scale in a cost-efficient manner while ensuring data sovereignty and data protection. The research area focuses its work on a use case in the area of federated learning for clinical data, taking into account data protection and security aspects. The goal is to create an end-to-end platform for efficient annotation that benefits both clinicians and the research community.
https://iml.dfki.de/news/end-to-end-active-learning-framework-for-medical-image-annotation/
Accenture Grant
The aim of this research project is to investigate the capabilities of ChatGPT with regard to Natural Language Inference (NLI) in the context of healthcare. The focus is on tasks such as understanding information from clinical trials and evidence-based review of healthcare data. Using various chain-of-thought methods research is being conducted to improve the reasoning capabilities of ChatGPT and to integrate dynamic context analysis techniques for higher inference accuracy. The approach includes mechanisms such as context analysis and multi-hop reasoning.
https://iml.dfki.de/news/research-grant-from-accenture/
