Explainable artificial intelligence approaches for COVID-19 prognosis prediction using clinical markers
K Chadaga, S Prabhu, N Sampathila, R Chadaga… - Scientific Reports, 2024 - nature.com
The COVID-19 influenza emerged and proved to be fatal, causing millions of deaths
worldwide. Vaccines were eventually discovered, effectively preventing the severe …
worldwide. Vaccines were eventually discovered, effectively preventing the severe …
Automated semantic lung segmentation in chest CT images using deep neural network
M Murugappan, AK Bourisly, NB Prakash… - Neural Computing and …, 2023 - Springer
Lung segmentation algorithms play a significant role in segmenting theinfected regions in
the lungs. This work aims to develop a computationally efficient and robust deep learning …
the lungs. This work aims to develop a computationally efficient and robust deep learning …
Deep Learning Framework for Liver Segmentation from T1-Weighted MRI Images
The human liver exhibits variable characteristics and anatomical information, which is often
ambiguous in radiological images. Machine learning can be of great assistance in …
ambiguous in radiological images. Machine learning can be of great assistance in …
SGD-based cascade scheme for higher degrees wiener polynomial approximation of large biomedical datasets
The modern development of the biomedical engineering area is accompanied by the
availability of large volumes of data with a non-linear response surface. The effective …
availability of large volumes of data with a non-linear response surface. The effective …
Prognostic model of ICU admission risk in patients with COVID-19 infection using machine learning
With the onset of the COVID-19 pandemic, the number of critically sick patients in intensive
care units (ICUs) has increased worldwide, putting a burden on ICUs. Early prediction of ICU …
care units (ICUs) has increased worldwide, putting a burden on ICUs. Early prediction of ICU …
[HTML][HTML] A hybrid contextual framework to predict severity of infectious disease: COVID-19 case study
Infectious disease is a particular type of disorder triggered by organisms and transmitted
directly or indirectly from an infected one like COVID-19. The global economy and public …
directly or indirectly from an infected one like COVID-19. The global economy and public …
Thresholding Chaotic Butterfly Optimization Algorithm with Gaussian Kernel (TCBOGK) based segmentation and DeTrac deep convolutional neural network for COVID …
AM Alhassan - Multimedia Tools and Applications, 2024 - Springer
The present panic issue all over world is COVID-19. Most perfect with quick identification of
COVID-19 is required to do superior decision that provides immediate treatment for the …
COVID-19 is required to do superior decision that provides immediate treatment for the …
Evidence-aware multi-modal data fusion and its application to total knee replacement prediction
Deep neural networks have been widely studied for predicting a medical condition, such as
total knee replacement (TKR). It has shown that data of different modalities, such as imaging …
total knee replacement (TKR). It has shown that data of different modalities, such as imaging …
A Classification Framework to Detect Sars Covid-19 Disease Using Feature Selection and Variant-Based Ensemble Learning
A Akhtar - International Journal of Computational and Innovative …, 2023 - ijcis.com
The hazardous COVID-19 pandemic has caused millions of deaths worldwide which depicts
the significance of an early screening of this infection in order to stop it from spreading. Real …
the significance of an early screening of this infection in order to stop it from spreading. Real …
Adaptive Stacking Ensemble Techniques for Early Severity Classification of COVID-19 Patients
During outbreaks of infectious diseases, such as COVID-19, it is critical to rapidly determine
treatment priorities and identify patients requiring hospitalization based on clinical severity …
treatment priorities and identify patients requiring hospitalization based on clinical severity …