📣 Help Shape the Future of UKRI's Gateway to Research (GtR)

We're improving UKRI's Gateway to Research and are seeking your input! If you would be interested in being interviewed about the improvements we're making and to have your say about how we can make GtR more user-friendly, impactful, and effective for the Research and Innovation community, please email gateway@ukri.org.

ADVANCING THE UNDERSTANDING OF CLINICAL SEPSIS USING GENE EXPRESSION-DRIVEN MACHINE LEARNING TO IMPROVE PATIENT OUTCOMES. (2024)

First Author: Rashid A

Attributed to: COG-MHEAR: Towards cognitively-inspired 5G-IoT enabled, multi-modal Hearing Aids funded by EPSRC

Abstract

No abstract provided

Bibliographic Information

Digital Object Identifier: http://dx.doi.org/10.1097/shk.0000000000002227

PubMed Identifier: 37752080

Publication URI: http://europepmc.org/abstract/MED/37752080

Type: Journal Article/Review

Volume: 61

Parent Publication: Shock (Augusta, Ga.)

Issue: 1

ISSN: 1073-2322