Efficient sepsis detection using deep learning and residual convolutional networks
Sepsis is a life-threatening complication caused by infection that leads to extensive tissue damage. If not treated promptly, it can become fatal. Early identification and diagnosis of sepsis are critical to improving patient outcomes. Although recent technological advancements have aided sepsis det...
Saved in:
Main Authors: | Ahmed S. Almasoud, Ghada Moh Samir Elhessewi, Munya A. Arasi, Abdulsamad Ebrahim Yahya, Menwa Alshammeri, Donia Badawood, Faisal Mohammed Nafie, Mohammed Assiri |
---|---|
Format: | Article |
Language: | English |
Published: |
PeerJ Inc.
2025-07-01
|
Series: | PeerJ Computer Science |
Subjects: | |
Online Access: | https://peerj.com/articles/cs-2958.pdf |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Real-Time Super Resolution Utilizing Dilation and Depthwise Separable Convolution
by: Che-Cheng Chang, et al.
Published: (2025-04-01) -
Where vultures fly /
by: Summers, Gerald
Published: (1974) -
Rolling Bearing Degradation Identification Method Based on Improved Monopulse Feature Extraction and 1D Dilated Residual Convolutional Neural Network
by: Chang Liu, et al.
Published: (2025-07-01) -
Masked Convolutions Within Skip Connections for Video Anomaly Detection
by: Demetris Lappas, et al.
Published: (2025-05-01) -
CSC-GCN: Contrastive semantic calibration for graph convolution network
by: Xu Yang, et al.
Published: (2023-11-01)