Sepsisdiagnose und -Vorhersage

Details

Veröffentlichungs-Nr.

EP4517775

Aktenzeichen

EP24172565

Anmeldetag

25. April 2024

Veröffentlichung

5. März 2025

Rechtsraum

EP

IPC

G16H50/20G16H50/70G16H50/30

Abstract

A computer-implemented method comprising: performing a prediction process comprising: based on input data comprising values of physiological measurement variables of a patient over a time period, computing first correlations in the input data, the computing comprising computing short range temporal correlations between values of physiological measurement variables at consecutive time steps using an attention-based mechanism and computing spatial correlations between values of different physiological measurement variables at a same time step using a self-attention mechanism; generating first updated node embeddings based on the input data and the first correlations, each node corresponding to a physiological measurement variable at a time step; using a recurrent neural network, RNN, updating the first updated node embeddings based on second correlations between the first updated node embeddings to generate temporally updated embeddings; and based on the temporally updated embeddings and using a neural network, NN, generating a prediction whether the patient will have sepsis.

Anmelder

Firma

FUJITSU LIMITED

Land

🇯🇵 Japan

Fachgebiete