Nephrology

Latest AI and machine learning research in nephrology for healthcare professionals.

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Autoencoder techniques for survival analysis on renal cell carcinoma.

Survival is the gold standard in oncology when determining the real impact of therapies in patients ...

Using Natural Language Processing and Machine Learning to classify the status of kidney allograft in Electronic Medical Records written in Spanish.

INTRODUCTION: Accurate identification of graft loss in Electronic Medical Records of kidney transpla...

StackAHTPs: An explainable antihypertensive peptides identifier based on heterogeneous features and stacked learning approach.

Hypertension, often known as high blood pressure, is a major concern to millions of individuals glob...

Application of machine learning algorithms in predicting new onset hypertension: a study based on the China Health and Nutrition Survey.

BACKGROUND: Hypertension is a serious chronic disease that can significantly lead to various cardiov...

Artificial Intelligence to Predict Chronic Kidney Disease Progression to Kidney Failure: A Narrative Review.

Chronic kidney disease is characterised by the progressive loss of kidney function. However, predict...

Prediction of Cisplatin-Induced Acute Kidney Injury Using an Interpretable Machine Learning Model and Electronic Medical Record Information.

Predicting cisplatin-induced acute kidney injury (Cis-AKI) before its onset is important. We aimed t...

RSNA 2023 Abdominal Trauma AI Challenge: Review and Outcomes.

Purpose To evaluate the performance of the winning machine learning models from the 2023 RSNA Abdomi...

[Identification of kidney stone types by deep learning integrated with radiomics features].

Currently, the types of kidney stones before surgery are mainly identified by human beings, which di...

Survival analysis of clear cell renal cell carcinoma based on radiomics and deep learning features from CT images.

PURPOSE: To create a nomogram for accurate prognosis of patients with clear cell renal cell carcinom...

Novel machine learning technique further clarifies unrelated donor selection to optimize transplantation outcomes.

We investigated the impact of donor characteristics on outcomes in allogeneic hematopoietic cell tra...

Predictive Capacities of a Machine Learning Decision Tree Model Created to Analyse Feasibility of an Open or Robotic Kidney Transplant.

BACKGROUND: Machine learning has emerged as a potent tool in healthcare. A decision tree model was b...

Live-Donor Kidney Transplant Outcome Prediction (L-TOP) using artificial intelligence.

BACKGROUND: Outcome prediction for live-donor kidney transplantation improves clinical and patient d...

A multi-modal fusion model with enhanced feature representation for chronic kidney disease progression prediction.

Artificial intelligence (AI)-based multi-modal fusion algorithms are pivotal in emulating clinical p...

Primary care research on hypertension: A bibliometric analysis using machine-learning.

Hypertension is one of the most important chronic diseases worldwide. Hypertension is a critical con...

High-dimensional Immune Profiles and Machine Learning May Predict Acute Myeloid Leukemia Relapse Early following Transplant.

Identification of early immune signatures associated with acute myeloid leukemia (AML) relapse follo...

Machine learning-driven in-hospital mortality prediction in HIV/AIDS patients with infection: a single-centred retrospective study.

() is a widely disseminated betaherpesvirus that typically induces latant infections. In immunocom...

Deep learning-based analysis of EGFR mutation prevalence in lung adenocarcinoma H&E whole slide images.

EGFR mutations are a major prognostic factor in lung adenocarcinoma. However, current detection meth...

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