Nephrology

End Stage Renal Disease

Latest AI and machine learning research in end stage renal disease for healthcare professionals.

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Nephrology Subcategories: Anemia End Stage Renal Disease
Showing 64-84 of 3,387 articles
DEPDC1B, CDCA2, APOBEC3B, and TYMS are potential hub genes and therapeutic targets for diagnosing dialysis patients with heart failure.

INTRODUCTION: Heart failure (HF) has a very high prevalence in patients with maintenance hemodialysi...

Identification of Factors Influencing Donor-Derived Cell-Free DNA Levels up to One Year After Kidney Transplant.

Donor-derived cell-free DNA (dd-cfDNA) in the peripheral blood of allograft recipients has shown to...

A machine learning tool for early identification of celiac disease autoimmunity.

Identifying which patients should undergo serologic screening for celiac disease (CD) may help diagn...

Hope for the best prepare for the worst: acute kidney disease and catastrophic comorbidities (a case report).

It is evident that Acute Kidney Injury (AKI) is an independent risk factor for both the survival of ...

Very low doses of rituximab in autoimmune hemolytic anemia-an open-label, phase II pilot trial.

INTRODUCTION: Although rituximab is approved for several autoimmune diseases, no formal dose finding...

Leveraging machine learning models for anemia severity detection among pregnant women following ANC: Ethiopian context.

BACKGROUND: Anemia during pregnancy is a significant public health concern, particularly in resource...

A potential predictive model based on machine learning and CPD parameters in elderly patients with aplastic anemia and myelodysplastic neoplasms.

BACKGROUND: Aplastic anemia (AA) and myelodysplastic neoplasms (MDS) have similar peripheral blood m...

elimination of antimicrobials during ADVanced Organ Support hemodialysis.

BACKGROUND: Acute kidney injury (AKI) requiring continuous renal replacement therapy is common in cr...

Predicting high-flow arteriovenous fistulas and cardiac outcomes in hemodialysis patients.

BACKGROUND: Heart failure is common in patients receiving hemodialysis. A high-flow arteriovenous fi...

Using machine learning models for predicting monthly iPTH levels in hemodialysis patients.

BACKGROUND AND OBJECTIVE: Intact parathyroid hormone (iPTH), also known as active parathyroid hormon...

Predicting early mortality in hemodialysis patients: a deep learning approach using a nationwide prospective cohort in South Korea.

Early mortality after hemodialysis (HD) initiation significantly impacts the longevity of HD patient...

Prediction of dialysis adequacy using data-driven machine learning algorithms.

BACKGROUND: Adequate delivery of hemodialysis (HD), measured by the spKt/V derived from urea reducti...

MultiThal-classifier, a machine learning-based multi-class model for thalassemia diagnosis and classification.

BACKGROUND: The differential diagnosis between iron deficiency anemia (IDA) and thalassemia trait (T...

Optimizing anemia management using artificial intelligence for patients undergoing hemodialysis.

Patients with end-stage kidney disease (ESKD) frequently experience anemia, and maintaining hemoglob...

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