Review
Biochemistry & Molecular Biology
Anastasia Poznyak, Nikolay K. Sadykhov, Andrey G. Kartuesov, Evgeny E. Borisov, Vasily N. Sukhorukov, Alexander N. Orekhov
Summary: Atherosclerosis is the leading cause of cardiovascular disease worldwide, and it shares several risk factors with chronic kidney disease. Patients with chronic kidney disease are more susceptible to cardiovascular problems.
Article
Radiology, Nuclear Medicine & Medical Imaging
Sangmi Lee, Myeongkyun Kang, Keunho Byeon, Sang Eun Lee, In Ho Lee, Young Ah Kim, Shin-Wook Kang, Jung Tak Park
Summary: This study assessed the effect of integrating computer-extracted measurable features with the convolutional neural network (CNN) on the ultrasound image CAD accuracy of CKD. The results showed that integrating measurable features into ultrasound image training models can significantly improve classification accuracy, especially when clinical information is included.
JOURNAL OF DIGITAL IMAGING
(2022)
Article
Transplantation
Takayuki Hamano, Takahiro Imaizumi, Takeshi Hasegawa, Naohiko Fujii, Hirotaka Komaba, Masahiko Ando, Masaomi Nangaku, Kosaku Nitta, Hideki Hirakata, Yoshitaka Isaka, Takashi Wada, Shoichi Maruyama, Masafumi Fukagawa
Summary: The CGA classification is more valuable than the GA classification in predicting kidney disease outcomes, and incorporating a prior biopsy-proven diagnosis significantly improves the accuracy of outcome prediction.
NEPHROLOGY DIALYSIS TRANSPLANTATION
(2023)
Article
Chemistry, Multidisciplinary
Weilun Wang, Goutam Chakraborty, Basabi Chakraborty
Summary: The study utilized 23 health-related features to predict creatinine value and evaluate the risk of CKD through regression modeling. Three machine learning models were used, and ensemble learning was employed to improve creatinine prediction accuracy.
APPLIED SCIENCES-BASEL
(2021)
Article
Health Care Sciences & Services
Surya Krishnamurthy, K. S. Kapeleshh, Erik Dovgan, Mitja Lustrek, Barbara Gradisek Piletic, Kathiravan Srinivasan, Yu-Chuan (Jack) Li, Anton Gradisek, Shabbir Syed-Abdul
Summary: This study developed a machine-learning model using data from Taiwan's National Health Insurance Research Database to predict the occurrence of CKD, with the Convolutional Neural Networks (CNN) model performing best. The model could assist policymakers in forecasting the trends of CKD in the population.
Article
Pediatrics
Paulo Cesar Koch Nogueira, Auberth Henrik Venson, Maria Fernanda Camargo de Carvalho, Tulio Konstantyner, Ricardo Sesso
Summary: The objective of this study was to use decision trees and extreme gradient boost models to predict the risk classification of pediatric patients with chronic kidney disease (CKD) and reveal the signs and symptoms associated with CKD. The study involved 376 CKD patients and a control group of healthy children. The decision tree model identified 6 variables associated with CKD, while the extreme gradient boost model identified 12 variables distinguishing CKD from healthy children. The extreme gradient boost model showed the highest accuracy (ROC AUC = 0.939, 95%CI: 0.911 to 0.977), followed by the decision tree model (ROC AUC = 0.896, 95%CI: 0.850 to 0.942).
EUROPEAN JOURNAL OF PEDIATRICS
(2023)
Article
Nutrition & Dietetics
Almudena Perez-Torres, Alberto Caverni-Munoz, Elena Gonzalez Garcia
Summary: Chronic kidney disease is a major public health issue and Mediterranean diet could be a suitable dietary option for patients. This review aims to provide practical guidelines on how to adapt Mediterranean diet for chronic kidney disease patients.
Article
Chemistry, Multidisciplinary
Deema Mohammed Alsekait, Hager Saleh, Lubna Abdelkareim Gabralla, Khaled Alnowaiser, Shaker El-Sappagh, Radhya Sahal, Nora El-Rashidy
Summary: Chronic kidney disease (CKD) is a condition where kidney function gradually declines. Early detection of CKD is crucial and treatment options include medication, hemodialysis, and kidney transplantation. Machine learning and deep learning models have gained importance in medical diagnosis for their high prediction accuracy. This study proposes a novel ensemble deep learning approach for CKD detection and uses various feature selection methods. Experimental results using the UCI machine learning repository demonstrate the superior performance of the proposed model compared to other models.
APPLIED SCIENCES-BASEL
(2023)
Article
Computer Science, Information Systems
Ping Liang, Jiannan Yang, Weilan Wang, Guanjie Yuan, Min Han, Qingpeng Zhang, Zhen Li
Summary: Early diagnosis and prediction of CKD progress are crucial for personalized treatment and improving patients' quality of life. This study explores the intelligibility of machine learning and deep learning models for ESRD prediction in CKD patients. The deep learning model achieves high accuracy and provides intelligible insights into CKD progression. This study provides solid data-driven evidence for using machine learning in CKD clinical management and treatment.
IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS
(2023)
Article
Computer Science, Artificial Intelligence
Sahar A. El-Rahman, Ala Saleh Alluhaidan, Reem A. AlRashed, Duna N. AlZunaytan
Summary: This paper presents a mobile application that analyzes patients' medical records and uses machine learning techniques to diagnose chronic conditions. The study shows that the tree algorithm achieves 100% accuracy for hypertension diagnosis, with the highest precision for both male and female datasets.
Article
Chemistry, Multidisciplinary
Luis Chaves, Goncalo Marques
Summary: The study explores the use of data mining techniques for early diagnosis of diabetes, with results indicating that Neural Networks should be used for diabetes prediction. The proposed model shows high predictive accuracy and specificity.
APPLIED SCIENCES-BASEL
(2021)
Article
Computer Science, Information Systems
Pankaj Chittora, Sandeep Chaurasia, Prasun Chakrabarti, Gaurav Kumawat, Tulika Chakrabarti, Zbigniew Leonowicz, Michal Jasinski, Lukasz Jasinski, Radomir Gono, Elzbieta Jasinska, Vadim Bolshev
Summary: This study discusses the prediction of Chronic Kidney Disease using machine learning techniques, with LSVM (with L2 penalty) achieving the highest accuracy of 98.86% in synthetic minority over-sampling technique with full features, and a deep neural network achieving the highest accuracy of 99.6% on the same dataset.
Article
Transplantation
Aghiles Hamroun, Luc Frimat, Maurice Laville, Marie Metzger, Christian Combe, Denis Fouque, Christian Jacquelinet, Carole Ayav, Sophie Liabeuf, Celine Lange, Yves-Edouard Herpe, Jarcy Zee, Francois Glowacki, Ziad A. Massy, Bruce Robinson, Benedicte Stengel
Summary: This study reveals the high incidence of hospital-acquired AKI events in patients with CKD and their underreporting at hospital discharge. It also identifies low birth weight and anemia as potential new risk factors in CKD patients.
NEPHROLOGY DIALYSIS TRANSPLANTATION
(2022)
Article
Immunology
Xiao Qi Liu, Ting Ting Jiang, Meng Ying Wang, Wen Tao Liu, Yang Huang, Yu Lin Huang, Feng Yong Jin, Qing Zhao, Gui Hua Wang, Xiong Zhong Ruan, Bi Cheng Liu, Kun Ling Ma
Summary: The study found that microinflammation is closely associated with potential cardiovascular disease events in CKD patients, suggesting that therapeutic strategies against microinflammation should be implemented to prevent CVD events in CKD patients treated with statins.
FRONTIERS IN IMMUNOLOGY
(2022)
Editorial Material
Endocrinology & Metabolism
Ankit B. Patel, Kavita Mistry, Ashish Verma
Summary: SGLT2 inhibitors have revolutionized the treatment of heart failure and diabetic kidney disease, showing kidney protection benefits independent of diabetes mellitus in both diabetic and non-diabetic patients, as demonstrated in the DAPA-CKD trial by Heerspink et al.
TRENDS IN ENDOCRINOLOGY AND METABOLISM
(2021)
Article
Engineering, Biomedical
Selahaddin Batuhan Akben
BIOCYBERNETICS AND BIOMEDICAL ENGINEERING
(2018)
Article
Engineering, Multidisciplinary
Selahaddin Batuhan Akben
Article
Engineering, Chemical
Omer Faruk Gamli, Zeliha Eraslan, Selahaddin Batuhan Akben
JOURNAL OF FOOD PROCESS ENGINEERING
(2018)
Article
Food Science & Technology
Duygu Balpetek Kulcu, Selin Kalkan, Selahaddin Batuhan Akben
JOURNAL OF FOOD PROCESSING AND PRESERVATION
(2019)
Article
Materials Science, Multidisciplinary
Ilhan Celik, Selahaddin Batuhan Akben, Ugur Mazlum
APPLIED PHYSICS A-MATERIALS SCIENCE & PROCESSING
(2019)
Article
Engineering, Biomedical
S. B. Akben
Article
Engineering, Chemical
Selin Kalkan, Selahaddin Batuhan Akben, Demet Canga
JOURNAL OF FOOD PROCESS ENGINEERING
(2019)
Article
Food Science & Technology
Esra Cavdir, Selahaddin B. Akben, Adnan Bozdogan
JOURNAL OF TEXTURE STUDIES
(2020)
Article
Engineering, Multidisciplinary
Selahaddin Batuhan Akben
INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN ENGINEERING
(2020)
Article
Chemistry, Physical
Ozkan Aydin, Pelin Atilla, Selahaddin Batuhan Akben, Murat Farsak
Summary: Catalyst development is crucial for system dynamics, and this study focuses on developing an efficient cathode material using electrochemical deposition. The IVER optimization method is used to determine the optimal deposition conditions and suspended solution concentration.
MOLECULAR CATALYSIS
(2022)
Article
Multidisciplinary Sciences
Kubilay Muhammed Sunnetci, Selahaddin Batuhan Akben, Mevlude Merve Kara, Ahmet Alkan
Summary: The COVID-19 pandemic has led to a global increase in cases, resulting in mandatory mask-wearing and cleaning rules. To address this, a system using GoogLeNet architecture was developed to automatically detect mask-wearing. By extracting image features and training classifiers, high accuracy in mask detection was achieved. The proposed system has practical utility and advantages in terms of complexity compared to object detection models.
GAZI UNIVERSITY JOURNAL OF SCIENCE
(2023)
Proceedings Paper
Computer Science, Artificial Intelligence
Selahaddin Batuhan Akben
2017 INTERNATIONAL ARTIFICIAL INTELLIGENCE AND DATA PROCESSING SYMPOSIUM (IDAP)
(2017)
Article
Multidisciplinary Sciences
Selahaddinb B. Akben
KUWAIT JOURNAL OF SCIENCE
(2017)
Article
Engineering, Biomedical
Selahaddin Batuhan Akben
BIOMEDICAL RESEARCH-INDIA
(2017)