The significance of machine learning in clinical disease diagnosis: A review
The global need for effective disease diagnosis remains substantial, given the complexities
of various disease mechanisms and diverse patient symptoms. To tackle these challenges …
of various disease mechanisms and diverse patient symptoms. To tackle these challenges …
[HTML][HTML] A comparative assessment of artificial intelligence models used for early prediction and evaluation of chronic kidney disease
Abstract Chronic Kidney Disease (CKD) is one of the most prevalent and fatal diseases
influencing people on a larger that remains dormant until irreversible damage has been …
influencing people on a larger that remains dormant until irreversible damage has been …
Diagnosis of chronic kidney disease using effective classification algorithms and recursive feature elimination techniques
EM Senan, MH Al-Adhaileh, FW Alsaade… - Journal of healthcare …, 2021 - Wiley Online Library
Chronic kidney disease (CKD) is among the top 20 causes of death worldwide and affects
approximately 10% of the world adult population. CKD is a disorder that disrupts normal …
approximately 10% of the world adult population. CKD is a disorder that disrupts normal …
[HTML][HTML] Chronic kidney disease prediction based on machine learning algorithms
Chronic kidney disease (CKD) is a dangerous ailment that can last a person's entire life and
is caused by either kidney malignancy or decreased kidney functioning. It is feasible to halt …
is caused by either kidney malignancy or decreased kidney functioning. It is feasible to halt …
Machine learning techniques for chronic kidney disease risk prediction
Chronic kidney disease (CKD) is a condition characterized by progressive loss of kidney
function over time. It describes a clinical entity that causes kidney damage and affects the …
function over time. It describes a clinical entity that causes kidney damage and affects the …
[HTML][HTML] Performance analysis of cost-sensitive learning methods with application to imbalanced medical data
Many real-world machine learning applications require building models using highly
imbalanced datasets. Usually, in medical datasets, the healthy patients or samples are …
imbalanced datasets. Usually, in medical datasets, the healthy patients or samples are …
A machine learning method with filter-based feature selection for improved prediction of chronic kidney disease
SA Ebiaredoh-Mienye, TG Swart, E Esenogho… - Bioengineering, 2022 - mdpi.com
The high prevalence of chronic kidney disease (CKD) is a significant public health concern
globally. The condition has a high mortality rate, especially in developing countries. CKD …
globally. The condition has a high mortality rate, especially in developing countries. CKD …
A comprehensive analysis on detecting chronic kidney disease by employing machine learning algorithms
MM Nishat, F Faisal, RR Dip… - … on Pervasive Health …, 2021 - publications.eai.eu
Abstract INTRODUCTION: Chronic Kidney Disease refers to the slow, progressive
deterioration of kidney functions. However, the impairment is irreversible and imperceptible …
deterioration of kidney functions. However, the impairment is irreversible and imperceptible …
Enhancing the early detection of chronic kidney disease: a robust machine learning model
MS Arif, A Mukheimer, D Asif - Big Data and Cognitive Computing, 2023 - mdpi.com
Clinical decision-making in chronic disorder prognosis is often hampered by high variance,
leading to uncertainty and negative outcomes, especially in cases such as chronic kidney …
leading to uncertainty and negative outcomes, especially in cases such as chronic kidney …
A robust chronic kidney disease classifier using machine learning
Clinical support systems are affected by the issue of high variance in terms of chronic
disorder prognosis. This uncertainty is one of the principal causes for the demise of large …
disorder prognosis. This uncertainty is one of the principal causes for the demise of large …