Analyzing chronic disease biomarkers using electrochemical sensors and artificial neural networks

K Sinha, Z Uddin, HI Kawsar, S Islam, MJ Deen… - TrAC Trends in …, 2023 - Elsevier
Chronic diseases are persistent health conditions that affect our quality of life, increase
morbidity and mortality, and are a global challenge. Further, the increasing prevalence of …

Machine learning models in breast cancer survival prediction

M Montazeri, M Montazeri, M Montazeri… - … and Health Care, 2016 - content.iospress.com
BACKGROUND: Breast cancer is one of the most common cancers with a high mortality rate
among women. With the early diagnosis of breast cancer survival will increase from 56% to …

HHFS: Hyper-heuristic feature selection

M Montazeri - Intelligent Data Analysis, 2016 - content.iospress.com
Feature selection is an important machine learning field which can provide a key role for the
challenging problem of classifying high-dimensional data. This problem is finding effective …

Futures studies in health: choosing the best intelligent data mining model to predict and diagnose liver Cancer in early stage

F Afzali, Z Heidari, M Montazeri, L Ahmadian… - Journal of Health and …, 2015 - jhbmi.ir
Method: In the present article, a retrospective study was conducted on 516 cases of primary
and secondary liver cancer, and 22 risk factors were examined. Data were collected from the …

Performance Analysis of State-of-the-Art Classifiers and Stack Ensemble Model for Liver Disease Diagnosis

B Sahu, S Agrawal, H Dey, C Raj - Biologically Inspired Techniques in …, 2022 - Springer
Around the world, liver disease is one of the leading causes of death. The number of
persons who suffer is steadily rising. It is vital to maintain a healthy liver to assist functions …

Comparison of machine-learning algorithms efficiency to build a predictive model for mortality risk in COVID-19 hospitalized patients.

M Shanbehzadeh, A Valinejadi, R Afrah… - 2022 - cabidigitallibrary.org
Introduction: The rapid worldwide outbreak of SARS-CoV-2 has posed serious and
unprecedented challenges to healthcare systems in predicting disease behavior and …

Memetic algorithm image enhancement for preserving mean brightness without losing image features

M Montazeri - International Journal of Image and Graphics, 2019 - World Scientific
In the image processing application, contrast enhancement is a major step. Conventional
contrast enhancement methods such as Histogram Equalization (HE) do not have …

Light Intensity Adjustment and Noise Removal for Medical Image Enhancement

M Montazeri - Journal of Health and Biomedical Informatics, 2016 - jhbmi.ir
Method: The methods used in this study to enhance medical images quality are categorized
into two groups; intensity adjustment and noise removal. Intensity adjustment methods …

ARTIFICIAL INTELLIGENCE TECHNIQUES IN PREDICTION OF COVID-19 MORTALITY AND ITS RELATED FACTORS: A MULTI-CENTER STUDY

A Payandeh, H Esmaily, M Salehi… - … and Applications in …, 2023 - pphmjopenaccess.com
Predictive artificial intelligence (AI) models for the assessment of factors and trends related
to disease prevalence, prognosis, and the risk prediction of mortality in the early phases …

Estimating survival rate of kidney transplants by using data mining.

L Shahmoradi, M Langarizadeh, G Pourmand, A Fard… - 2017 - cabidigitallibrary.org
Introduction: todays, kidney failure is one of the costly problems of human society and use of
renal replacement therapy is increasing in the world and Iran. Survival analysis is one of the …