An explainable artificial intelligence model proposed for the prediction of myalgic encephalomyelitis/chronic fatigue syndrome and the identification of distinctive …

FH Yagin, A Alkhateeb, A Raza, NA Samee… - Diagnostics, 2023 - mdpi.com
Background: Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a complex
and debilitating illness with a significant global prevalence, affecting over 65 million …

A proposed tree-based explainable artificial intelligence approach for the prediction of angina pectoris

E Guldogan, FH Yagin, A Pinar, C Colak, S Kadry… - Scientific Reports, 2023 - nature.com
Cardiovascular diseases (CVDs) are a serious public health issue that affects and is
responsible for numerous fatalities and impairments. Ischemic heart disease (IHD) is one of …

Estimation of obesity levels through the proposed predictive approach based on physical activity and nutritional habits

HG Gozukara Bag, FH Yagin, Y Gormez, PP González… - Diagnostics, 2023 - mdpi.com
Obesity is the excessive accumulation of adipose tissue in the body that leads to health
risks. The study aimed to classify obesity levels using a tree-based machine-learning …

Comparative effectiveness of 10-week equipment-based pilates and diaphragmatic breathing exercise on heart rate variability and pulmonary function in young adult …

S Adıgüzel, D Aras, M Gülü, MI Aldhahi… - BMC Sports Science …, 2023 - Springer
Background The positive effects of Pilates and slow-controlled breathing exercises on health
are examined in different studies. The purpose of the study was to investigate the effects of …

Analysis of hematological indicators via explainable artificial intelligence in the diagnosis of acute heart failure: a retrospective study

R Yilmaz, FH Yagin, C Colak, K Toprak… - Frontiers in …, 2024 - frontiersin.org
Introduction Acute heart failure (AHF) is a serious medical problem that necessitates
hospitalization and often results in death. Patients hospitalized in the emergency department …

A Deep Learning Neural Network to Classify Obesity Risk in Portuguese Adolescents Based on Physical Fitness Levels and Body Mass Index Percentiles: Insights for …

P Forte, S Encarnação, AM Monteiro, JE Teixeira… - Behavioral …, 2023 - mdpi.com
The increasing prevalence of overweight and obesity among adults is a risk factor for many
chronic diseases and death. In addition, obesity among children and adolescents has …

[HTML][HTML] An early sepsis prediction model utilizing machine learning and unbalanced data processing in a clinical context

L Zhou, M Shao, C Wang, Y Wang - Preventive Medicine Reports, 2024 - Elsevier
Background Early and accurate diagnoses of sepsis patients are essential to reduce the
mortality. However, the sepsis is still diagnosed in a traditional way in China despite the …

Classification of Motor Competence in Schoolchildren Using Wearable Technology and Machine Learning with Hyperparameter Optimization

J Sulla-Torres, A Calla Gamboa… - Applied Sciences, 2024 - mdpi.com
Determining the classification of motor competence is an essential aspect of physical activity
that must be carried out during school years. The objective is to evaluate motor competence …

Optimize edilmiş denetimli öğrenme algoritmaları ile obezite analizi ve tahmini

T Turan - Mehmet Akif Ersoy Üniversitesi Fen Bilimleri Enstitüsü …, 2023 - dergipark.org.tr
Obezite dünya genelinde gerçekleşen ölümlerin en önemli beşinci nedeni olarak karşımız
çıkan bir sağlık sorunudur. Dünya Sağlık Örgütü (DSÖ) 2022 yılında yayınladığı raporda …

Predicting Obesity Levels with High Accuracy: Insights from a CatBoost Machine Learning Model

A Maulana, RPF Afidh, NB Maulydia… - Infolitika Journal of …, 2024 - heca-analitika.com
This study aims to develop a machine learning model using the CatBoost algorithm to
predict obesity based on demographic, lifestyle, and health-related features and compare its …