End Stage Renal Disease

Machine learning models to predict ICU admission of patients with COPD and depression: A retrospective cohort study.

This study aimed to develop and validate a machine learning (ML)-based predictive model to identify risk factors associated with intensive care unit (ICU) admission among patients with comorbid Chronic Obstructive Pulmonary Disease (COPD) and depression. Data of patients diagnosed with both COPD and depression were extracted from the MIMIC-IV version 3.1 database. A total of 1121 patients with fir...

Immunosuppressive regimens and long-term kidney transplant outcomes: A dual survival modeling framework.

Optimizing immunosuppressive therapy remains central to improving long-term outcomes after kidney transplantation. Both induction and maintenance therapies are widely used, yet their comparative effectiveness across diverse recipient populations requires further evaluation. This national retrospective cohort study analyzed 228,855 deceased-donor kidney transplant recipients using data from 2000-20...

Skin microbiome signatures track uremic pruritus severity in hemodialysis patients.

Chronic kidney disease-associated pruritus (CKD-aP) is frequent in patients receiving maintenance hemodialysis and is often difficult to control. Whil...

Impact of machine learning on spare parts availability for critical medical devices: a supervised machine learning perspective.

PURPOSE: This paper seeks to improve the reliability and quality of operation of the critical medical equipment methods through the combination of fai...

Frailty index and type 2 diabetes with renal complications: insights from Mendelian randomization and retrospective observational study.

OBJECTIVES: To investigate the relationship between frailty and diabetic kidney disease (DKD)-related renal complications using Mendelian randomizatio...

Predicting intradialytic exercise intolerance in maintenance hemodialysis patients: an interpretable machine learning approach integrating functional assessments.

Exercise intolerance, primarily manifesting as intradialytic hypotension (IDH), is common in maintenance hemodialysis patients, interrupting intervent...

Validation of online clearance monitoring and machine learning-based prediction of dialysis adequacy in Vietnamese hemodialysis patients: a cross-sectional study.

BACKGROUND: Online clearance monitoring (OCM) offers non-invasive real-time dialysis adequacy assessment, but validation data from Southeast Asian pop...

Development of an anemia detection model in emergency departments using lip region images based on medical knowledge and deep learning technology.

Anemia's high global prevalence and socio-economic burden necessitate early diagnosis, yet reliance on invasive blood testing creates significant barr...

A smart nutrition system for vitamin B12 deficiency management from sensing to precision intervention.

Vitamin B12 is essential for neural function, red blood cell formation, and DNA synthesis, yet its deficiency persists as a global health burden drivi...

Reply - Letter to the editor: Comment on "Explainable Electronic Medical Record-Based Machine Learning to Predict 1-Year Incident Protein-Energy Wasting in Non-Dialysis Chronic Kidney Disease: A Single-Center Development Study".

Diagnostic performance of discriminant formulas and machine learning models for detecting β-thalassemia trait in Bangladesh.

BACKGROUND: β-thalassemia poses a considerable public health burden in Bangladesh, where a high carrier frequency underlies widespread disease risk. I...

Comment on "Explainable Electronic Medical Record-Based Machine Learning to Predict 1-Year Incident Protein-Energy Wasting in Non-Dialysis Chronic Kidney Disease: A Single-Center Development Study".

Transforming hemodialysis care: a tripartite collaboration model among medical staff, AI agents, and robots.

Hemodialysis demand is rising as populations age and the chronic kidney disease burden increases, yet dialysis units face persistent workforce constra...

Age-stratified risk profiles for emergency colorectal cancer resection: A machine-learning analysis.

BACKGROUND: Emergency colorectal cancer resection (ECCR) is associated with worse perioperative and oncologic outcomes than elective surgery. As the i...

Development and internal validation of a clinical prediction model for hemodialysis-related headache using LASSO and Boruta feature selection.

A common neurological symptom in dialysis patients is hemodialysis-related headache (HRH), which can result in premature hemodialysis termination and ...

Large language models for generating longitudinal synthetic data in low-risk pregnancy care.

This article describes an obstetric dataset covering the full continuum of care of 5000 synthetic low-risk pregnant women, from preconception to post-...

Predicting and explaining poor prognosis in diabetic kidney disease using SHAP-based interpretable machine learning.

Prognostic assessment of diabetic kidney disease (DKD) is essential for personalized management. This study developed eight machine learning models us...

Development and validation of a machine learning-based prediction model for malnutrition risk in peritoneal dialysis patients: a multi‑center retrospective study.

PURPOSE: To develop and validate a machine learning (ML)‑based model for predicting malnutrition risk in patients undergoing maintenance peritoneal di...

Predicting End-Stage Renal Disease and Mortality in Chronic Kidney Disease Using Machine Learning: Retrospective Cohort Study.

BACKGROUND: Chronic kidney disease (CKD) is a global health burden characterized by heterogeneous progression trajectories. Without timely and appropr...

Artificial intelligence system for anatomical landmark detection in rectovaginal fistula repair surgery: technical development and educational evaluation.

PURPOSE: Rectovaginal fistula from perineal body injury during delivery is rare, with limited case volumes preventing standardized protocols. We devel...