Back to search

Article

Self-Supervised Multi-Modal Transformer for Early Brain Tumor Prediction Using Super-Resolution MRI and ICU Time-Series Data

2026-08-15

Abstract excerpt

<title>Abstract</title> <p>Early and accurate detection of brain tumors remains one of the most challenging and consequential problems in clinical neuroscience and critical care medicine. Conventional diagnostic pipelines rely heavily on expert radiological interpretation of single-modality MRI scans, often overlooking the rich temporal and physiological information embedded in Intensive Care Unit (ICU) monitorin...

Topics

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

Identifiers and source

Literature Corpus work
8ba768d6-fabf-5f59-81fd-940f34c8486d
DOI
10.21203/rs.3.rs-10532727/v1
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.
Self-Supervised Multi-Modal Transformer for Early Brain Tumor Prediction Using Super-Resolution MRI and ICU Time-Series DataDOI 10.21203/rs.3.rs-10532727/v1
Select a neighboring publication to make it the new centre.