The invention

The invention

Recurr-NET: A multimodal pre-operative image-based deep-learning model for predicting hepatocellular carcinoma outcomes

M: Medicine – Surgery – Orthopaedics – Material for disabled

Informations

Stand number
B79
Exhibition class
M: Medicine – Surgery – Orthopaedics – Material for disabled
Technical description
Multimodal deep-learning model which integrates imaging and clinical data for predicting primary liver cancer (hepatocellular carcinoma) outcomes after surgery. It has superior performance to established scores and histology markers for prognostication.
Simplified description
We have created a computer model that uses images and medical information to predict outcomes after liver cancer surgery. It is more accurate than the traditional methods used to estimate these outcomes.

Inventors

Wai-Kay SETO
Wai-Kay SETO
inventor 3727293023_3317
The University of Hong Kong
The University of Hong Kong
inventor 3727293023_3106

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