Stroke risk prediction with machine learning techniques

E Dritsas, M Trigka - Sensors, 2022 - mdpi.com
A stroke is caused when blood flow to a part of the brain is stopped abruptly. Without the
blood supply, the brain cells gradually die, and disability occurs depending on the area of …

[HTML][HTML] A comparative assessment of artificial intelligence models used for early prediction and evaluation of chronic kidney disease

R Sawhney, A Malik, S Sharma, V Narayan - Decision Analytics Journal, 2023 - Elsevier
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 …

Data-driven machine-learning methods for diabetes risk prediction

E Dritsas, M Trigka - Sensors, 2022 - mdpi.com
Diabetes mellitus is a chronic condition characterized by a disturbance in the metabolism of
carbohydrates, fats and proteins. The most characteristic disorder in all forms of diabetes is …

Application of XGBoost model for early prediction of earthquake magnitude from waveform data

A Joshi, C Vishnu, CK Mohan, B Raman - Journal of Earth System …, 2023 - Springer
In this paper, a scalable end-to-end tree boosting system called XGBoost has been applied
for predicting the magnitude of an earthquake from the early part of earthquake waveform …

Cost-sensitive learning for imbalanced medical data: a review

I Araf, A Idri, I Chairi - Artificial Intelligence Review, 2024 - Springer
Abstract Integrating Machine Learning (ML) in medicine has unlocked many opportunities to
harness complex medical data, enhancing patient outcomes and advancing the field …

Comprehensive performance assessment of deep learning models in early prediction and risk identification of chronic kidney disease

S Akter, A Habib, MA Islam, MS Hossen… - IEEE …, 2021 - ieeexplore.ieee.org
The incidence of chronic kidney disease (CKD) is rising rapidly around the globe.
Asymptomatic CKD is common and guideline-directed monitoring to predict CKD by various …

Machine learning methods for hypercholesterolemia long-term risk prediction

E Dritsas, M Trigka - Sensors, 2022 - mdpi.com
Cholesterol is a waxy substance found in blood lipids. Its role in the human body is helpful in
the process of producing new cells as long as it is at a healthy level. When cholesterol …

[Retracted] Early Detection and Diagnosis of Chronic Kidney Disease Based on Selected Predominant Features

Z Ullah, M Jamjoom - Journal of healthcare engineering, 2023 - Wiley Online Library
In numerous perilous cases, a quick medical decision is needed for the early detection of
chronic diseases to avoid austere consequences that may be fatal. Chronic kidney disease …

[HTML][HTML] Explainable machine learning techniques to predict amiodarone-induced thyroid dysfunction risk: multicenter, retrospective study with external validation

YT Lu, HJ Chao, YC Chiang, HY Chen - Journal of Medical Internet …, 2023 - jmir.org
Background Machine learning offers new solutions for predicting life-threatening,
unpredictable amiodarone-induced thyroid dysfunction. Traditional regression approaches …

Profit scoring for credit unions using the multilayer perceptron, XGBoost and TabNet algorithms: Evidence from Peru

R Asencios, C Asencios, E Ramos - Expert Systems with Applications, 2023 - Elsevier
Credit unions are growing microfinance institutions that base their lending decisions on the
judgment of their credit analysts. Therefore, the purpose of this paper is to design 6 profit …