Background: Liver diseases are widespread and can have life-threatening consequences, requiring new approaches to diagnosis and treatment.
Aim: Develop and validate computer-based methods for diagnosis and prediction of unfavourable courses in liver diseases.
Methods: Evaluation of histological images from liver biopsies and clinical data by means of deep learning with artificial neural networks.
Application: Develop and test a prototype of an online platform for decentralised provision of deep learning methods.
Longterm goal: Offer a tool that will improve individual risk prediction and accelerate the diagnosis of rare diseases.
Presentation by Tom Lüdde at the EASL Digital Liver Cancer Summit 5–6 Feb 2021: