Diagnosis and risk stratification of liver disease using deep learning on routine clinical data
The Project
Background: Liver diseases are widespread and can have life-threatening consequences, necessitating 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 using deep learning.
Application: Develop and test a prototype of a web-based platform for decentralised provision of deep learning methods.
Long-term goal: Offer a tool that will improve individual risk prediction and accelerate the diagnosis of rare diseases.