End Stage Renal Disease

Prediction of myeloid malignant cells in Fanconi anemia using machine learning.

Fanconi anemia (FA) is an inherited bone marrow failure syndrome with cancer predisposition. Most FA patients develop aplastic anemia during childhood and have an extremely high cumulative risk to develop cancer during their lifespan. Myeloid malignancy is one of the main neoplastic risks for patients with FA, including high-risk myelodysplastic syndrome (MDS), recently renamed as myelodysplastic ...

The effect of air pollution and household environmental indicators on anemia status among under-five children in low-middle income countries: exploring potential machine learning applications on demographic and health surveys.

Exposure to air pollution has been associated with anemia in children, but little effort has been made in low- and middle-income countries (LMICs) in which the prevalence of anemia is persistently high. This study aimed to assess the effects of air pollution and household environmental indicators on anemia among children aged 6-59 months using machine learning algorithms. The Demographic and Healt...

Gene Modification: Exploring the potential in treating kidney diseases.

Chronic kidney disease (CKD) is a leading cause of death worldwide. Currently available drugs slow but do not cure or prevent progression to end-stage...

Predicting the Future Burden of Renal Replacement Therapy in Türkiye Using National Registry Data and Comparative Modeling Approaches.

BACKGROUND: Chronic kidney disease is a growing public health problem worldwide, and the number of patients requiring renal replacement therapy is ste...

Comparing ACES AP0 and AP1 color primaries for smartphone colorimetry in detecting soil CO2 leakage with a beetroot (Beta vulgaris) biosensor.

Effective monitoring of CO2 leaks from carbon capture and storage (CCS) sites is vital to mitigate environmental risks, including soil acidification a...

Acceptance of communication robots among patients undergoing maintenance hemodialysis with psychological stress.

OBJECTIVE: Although several psychotherapeutic interventions have been introduced for patients receiving maintenance hemodialysis (MHD), challenges suc...

Predicting postoperative length of stay: a feature selection approach to predictive modeling in lumbar fusion surgery.

BACKGROUND: Predictive modeling has the potential to improve preoperative planning and resource allocation in lumbar fusion surgery. This study aimed ...

DGPCNet: anemia detection from multimodal palm, fingernails, and eye conjunctiva images using deep global pyramid convolutional network.

BACKGROUND: Anemia is one of the most common hematological disorders causing fatigue, increased vulnerability to infection, low birth weight, and thre...

The Application of Machine-Learning Algorithms for Multiclass Classification of Microcytic Anemia Revealed That a Minimum Required Number of Hematological Parameters Is Enough to Achieve High Diagnostic Accuracy.

INTRODUCTION: Thalassemia is a major global health concern, as declared by the World Health Organization (WHO). Accurate screening of heterozygotes is...

Current status and future directions for the use of artificial intelligence in pediatric critical care nephrology.

Artificial intelligence (AI) has the potential to significantly improve the practice of medicine. However, its application in pediatric critical care ...

Advancing Anemia Detection With Deep Neural Networks: A Comparative Analysis of Training Strategies Using Conjunctival Images.

Learning curve for fenestrated-branched endovascular aortic repair using machine learning: A prospective national multicenter registry study.

OBJECTIVE: Fenestrated-branched endovascular aortic repair (F-BEVAR) is a complex procedure that requires significant experience and advanced technica...

Deep-Learning Virtual Superior Mesenteric Artery Modeling for Risk Stratification in Pancreas Surgery.

BACKGROUND: Understanding the patient-specific anatomy of the superior mesenteric artery (SMA) and its branches is of critical importance when perform...

Artificial intelligence in nephrology: predicting CKD progression and personalizing treatment.

Chronic kidney disease (CKD) represents a major and expanding global health challenge, with prevalence rising due to aging populations, diabetes, hype...

Responsible Use of Artificial Intelligence to Improve Kidney Care: A Statement from the American Society of Nephrology.

Artificial intelligence (AI) is rapidly transforming the delivery of kidney care through predictive analytics, machine learning, deep learning, and ge...

"PD-PREDICT": A Machine Learning Model for Patient Survival in Peritoneal Dialysis.

Accurate survival prediction in peritoneal dialysis (PD) patients is essential for personalized treatment planning and shared decision-making. We deve...

Machine Learning-Based Prediction of β-Thalassemia Trait Using Red Blood Cell Indices.

OBJECTIVES: Anemia is a significant global health concern, with hypochromic microcytic anemia being the most common type. Among its causes, β-thalasse...

Precision Nutritional Genomics, Gut Microbiota and Artificial Intelligence in Chronic Kidney Disease.

Chronic kidney disease (CKD) is a prevalent global health issue, and nutritional management of CKD is an integral component through all stages of the ...

Development of an interpretable machine learning model to predict short-term bleeding risk in patients receiving dual antithrombotic therapy following cardiac surgery.

INTRODUCTION: Bleeding is a serious complication in cardiac surgery, especially among patients receiving combined anticoagulant and antiplatelet thera...

AI-powered insights in pediatric nephrology: current applications and future opportunities.

Artificial intelligence (AI) is rapidly emerging as a transformative force in pediatric nephrology, enabling improvements in diagnostic accuracy, ther...