Rise of deep learning clinical applications and challenges in omics data: a systematic review
MA Mohammed, KH Abdulkareem, AM Dinar… - Diagnostics, 2023 - mdpi.com
This research aims to review and evaluate the most relevant scientific studies about deep
learning (DL) models in the omics field. It also aims to realize the potential of DL techniques …
learning (DL) models in the omics field. It also aims to realize the potential of DL techniques …
Fuzzy theory in fog computing: review, taxonomy, and open issues
Geographically dispersed Fog Computing architecture ubiquitously connected to a range of
heterogeneous nodes at the edge of the network can provide cooperative flexible, and …
heterogeneous nodes at the edge of the network can provide cooperative flexible, and …
Early health prediction framework using XGBoost ensemble algorithm in intelligent environment
Amidst the COVID-19 humanitarian catastrophe, the Internet of Things and Artificial
Intelligence (AI) are premier technologies in the healthcare domain that have emerged to a …
Intelligence (AI) are premier technologies in the healthcare domain that have emerged to a …
E-AVOA-TS: Enhanced African vultures optimization algorithm-based task scheduling strategy for fog–cloud computing
R Ghafari, N Mansouri - Sustainable Computing: Informatics and Systems, 2023 - Elsevier
In fog computing, inefficient scheduling of user tasks causes more delays. Moreover, how to
schedule tasks that need to be offloaded to fog nodes or cloud nodes has not been fully …
schedule tasks that need to be offloaded to fog nodes or cloud nodes has not been fully …
A new fog computing resource management (FRM) model based on hybrid load balancing and scheduling for critical healthcare applications
Critical healthcare application tasks require a real-time response because it affects patients'
life. Fog computing is the best solution to get a fast response and less energy consumption …
life. Fog computing is the best solution to get a fast response and less energy consumption …
[HTML][HTML] Bayesian machine learning analysis with Markov Chain Monte Carlo techniques for assessing characteristics and risk factors of Covid-19 in Erbil City-Iraq …
The study aims to showcase machine learning techniques in the application of medical
datasets for improving identification of correlations and relationships between variables …
datasets for improving identification of correlations and relationships between variables …
MEF: multidimensional examination framework for prioritization of COVID-19 severe patients and promote precision medicine based on hybrid multi-criteria decision …
Effective prioritization plays critical roles in precision medicine. Healthcare decisions are
complex, involving trade-offs among numerous frequently contradictory priorities …
complex, involving trade-offs among numerous frequently contradictory priorities …
Evaluating three machine learning classification methods for effective COVID-19 diagnosis
SARS-CoV2, which produces COVID-19, has spread worldwide. Since the number of
patients is rising daily, it requires time to evaluate laboratory data, limiting treatment and …
patients is rising daily, it requires time to evaluate laboratory data, limiting treatment and …
Event-specific transmission forecasting of SARS-CoV-2 in a mixed-mode ventilated office room using an ANN
The emerging novel variants and re-merging old variants of SARS-CoV-2 make it critical to
study the transmission probability in mixed-mode ventilated office environments. Artificial …
study the transmission probability in mixed-mode ventilated office environments. Artificial …
Optimised Internet of Thing framework based hybrid meta‐heuristic algorithms for E‐healthcare monitoring
M Al‐Hashimi, S Mohammed Jameel… - IET …, 2022 - Wiley Online Library
Everything can be connected in the Internet of Things (IoTs) technology that enables efficient
communication between connected objects. IoTs industry‐based meta‐heuristic and mining …
communication between connected objects. IoTs industry‐based meta‐heuristic and mining …