Back to search

Article

scCaT: an explainable capsulating architecture for sepsis diagnosis transferring from single-cell RNA sequencing

2024-04-20

Abstract excerpt

Sepsis is a life-threatening condition characterized by an exaggerated immune response to pathogens, leading to organ damage and high mortality rates in the intensive care unit. Although deep learning has achieved impressive performance on prediction and classification tasks in medicine, it requires large amounts of data and lacks explainability, which hinder its application to sepsis diagnosis. We introduce a dee...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work
87c750c8-9754-550b-815f-b68810ae842c
DOI
10.1101/2024.04.17.590014
Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest
Interactive article relationship graphSelect a related publication card to move it into the centre and load its closest explainable connections. Solid lines are source-backed structured connections. Dashed lines are semantic discovery signals and are not scientific evidence.
scCaT: an explainable capsulating architecture for sepsis diagnosis transferring from single-cell RNA sequencingDOI 10.1101/2024.04.17.590014
Select a neighboring publication to make it the new centre.