Machine learning-based early prediction of sepsis using electronic health records: a systematic review
Background: Sepsis, a life-threatening infection-induced inflammatory condition, has
significant global health impacts. Timely detection is crucial for improving patient outcomes …
significant global health impacts. Timely detection is crucial for improving patient outcomes …
A deep learning approach for parkinson's disease severity assessment
T Aşuroğlu, H Oğul - Health and Technology, 2022 - Springer
Abstract Purpose Parkinson's Disease comes on top among neurodegenerative diseases
affecting 10 million worldwide. To detect Parkinson's Disease in a prior state, gait analysis is …
affecting 10 million worldwide. To detect Parkinson's Disease in a prior state, gait analysis is …
Sepsis prediction in intensive care unit based on genetic feature optimization and stacked deep ensemble learning
Sepsis is a life-threatening disease that is associated with organ dysfunction. It occurs due to
the body's dysregulated response to infection. It is difficult to identify sepsis in its early …
the body's dysregulated response to infection. It is difficult to identify sepsis in its early …
Computational Intelligence-Based Disease Severity Identification: A Review of Multidisciplinary Domains
Disease severity identification using computational intelligence-based approaches is
gaining popularity nowadays. Artificial intelligence and deep-learning-assisted approaches …
gaining popularity nowadays. Artificial intelligence and deep-learning-assisted approaches …
PregGAN: A prognosis prediction model for breast cancer based on conditional generative adversarial networks
F Zhang, Y Zhang, X Zhu, X Chen, H Du… - Computer Methods and …, 2022 - Elsevier
Abstract Background and Objective: Generative adversarial network (GAN) is able to learn
from a set of training data and generate new data with the same characteristics as the …
from a set of training data and generate new data with the same characteristics as the …
Clinical applications of machine learning in the survival prediction and classification of sepsis: coagulation and heparin usage matter
Background Sepsis is a life-threatening syndrome eliciting highly heterogeneous host
responses. Current prognostic evaluation methods used in clinical practice are …
responses. Current prognostic evaluation methods used in clinical practice are …
Early prediction of sepsis using double fusion of deep features and handcrafted features
Y Duan, J Huo, M Chen, F Hou, G Yan, S Li, H Wang - Applied Intelligence, 2023 - Springer
Sepsis is a life-threatening medical condition that is characterized by the dysregulated
immune system response to infections, having both high morbidity and mortality rates. Early …
immune system response to infections, having both high morbidity and mortality rates. Early …
Classifying sepsis from photoplethysmography
S Lombardi, P Partanen, P Francia, I Calamai… - … Information Science and …, 2022 - Springer
Purpose Sepsis is a life-threatening organ dysfunction. It is caused by a dysregulated
immune response to an infection and is one of the leading causes of death in the intensive …
immune response to an infection and is one of the leading causes of death in the intensive …
MGP-AttTCN: An interpretable machine learning model for the prediction of sepsis
With a mortality rate of 5.4 million lives worldwide every year and a healthcare cost of more
than 16 billion dollars in the USA alone, sepsis is one of the leading causes of hospital …
than 16 billion dollars in the USA alone, sepsis is one of the leading causes of hospital …
Exploring a global interpretation mechanism for deep learning networks when predicting sepsis
EAT Strickler, J Thomas, JP Thomas, B Benjamin… - Scientific Reports, 2023 - nature.com
The purpose of this study is to identify additional clinical features for sepsis detection
through the use of a novel mechanism for interpreting black-box machine learning models …
through the use of a novel mechanism for interpreting black-box machine learning models …