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.

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