Klinik für Gastroenterologie, Hepatologie und Infektiologie

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The Project

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.

 


News:

Presentation by Tom Lüdde at the EASL Digital Liver Cancer Summit 5–6 Feb 2021:

The role of artificial intelligence or deep learning for the early diagnosis of HCC.


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