Biomarkers: Promising and valuable tools towards diagnosis, prognosis and treatment of Covid-19 and other diseases
The use of biomarkers as early warning systems in the evaluation of disease risk has
increased markedly in the last decade. Biomarkers are indicators of typical biological …
increased markedly in the last decade. Biomarkers are indicators of typical biological …
[HTML][HTML] Machine learning approaches in COVID-19 diagnosis, mortality, and severity risk prediction: A review
The existence of widespread COVID-19 infections has prompted worldwide efforts to control
and manage the virus, and hopefully curb it completely. One important line of research is the …
and manage the virus, and hopefully curb it completely. One important line of research is the …
The importance of being external. methodological insights for the external validation of machine learning models in medicine
Abstract Background and Objective Medical machine learning (ML) models tend to perform
better on data from the same cohort than on new data, often due to overfitting, or co-variate …
better on data from the same cohort than on new data, often due to overfitting, or co-variate …
Detecting COVID-19 patients based on fuzzy inference engine and Deep Neural Network
COVID-19, as an infectious disease, has shocked the world and still threatens the lives of
billions of people. Recently, the detection of coronavirus (COVID-19) is a critical task for the …
billions of people. Recently, the detection of coronavirus (COVID-19) is a critical task for the …
Review on the evaluation and development of artificial intelligence for COVID-19 containment
Artificial intelligence has significantly enhanced the research paradigm and spectrum with a
substantiated promise of continuous applicability in the real world domain. Artificial …
substantiated promise of continuous applicability in the real world domain. Artificial …
Artificial intelligence techniques to predict the airway disorders illness: a systematic review
Airway disease is a major healthcare issue that causes at least 3 million fatalities every year.
It is also considered one of the foremost causes of death all around the globe by 2030 …
It is also considered one of the foremost causes of death all around the globe by 2030 …
Accurate detection of Covid-19 patients based on Feature Correlated Naïve Bayes (FCNB) classification strategy
The outbreak of Coronavirus (COVID-19) has spread between people around the world at a
rapid rate so that the number of infected people and deaths is increasing quickly every day …
rapid rate so that the number of infected people and deaths is increasing quickly every day …
Automatic detection of severely and mildly infected COVID-19 patients with supervised machine learning models
MT Huyut - IRBM, 2023 - Elsevier
Objectives When the prognosis of COVID-19 disease can be detected early, the intense-
pressure and loss of workforce in health-services can be partially reduced. The primary …
pressure and loss of workforce in health-services can be partially reduced. The primary …
Machine learning sensors for diagnosis of COVID-19 disease using routine blood values for internet of things application
Healthcare digitalization requires effective applications of human sensors, when various
parameters of the human body are instantly monitored in everyday life due to the Internet of …
parameters of the human body are instantly monitored in everyday life due to the Internet of …
BMPA-TVSinV: A Binary Marine Predators Algorithm using time-varying sine and V-shaped transfer functions for wrapper-based feature selection
Z Beheshti - Knowledge-Based Systems, 2022 - Elsevier
The feature selection problem is one of the pre-processing mechanisms to find the optimal
subset of features from a dataset. The search space of the problem will exponentially grow …
subset of features from a dataset. The search space of the problem will exponentially grow …