Nephrology

A machine learning-based approach for predicting the outbreak of cardiovascular diseases in patients on dialysis.

BACKGROUND AND OBJECTIVE: Patients with End- Stage Kidney Disease (ESKD) have a unique cardiovascular risk. This study aims at predicting, with a certain precision, death and cardiovascular diseases in dialysis patients.

Toward automatic prediction of EGFR mutation status in pulmonary adenocarcinoma with 3D deep learning.

To develop a deep learning system based on 3D convolutional neural networks (CNNs), and to automatically predict EGFR-mutant pulmonary adenocarcinoma in CT images. A dataset of 579 nodules with EGFR mutation status labels of mutant (Mut) or wild-type (WT) was retrospectively analyzed. A deep learning system, namely 3D DenseNets, was developed to process 3D patches of nodules from CT data, and lear...

Analysis of parameters affecting blood oxygen saturation and modeling of fuzzy logic system for inspired oxygen prediction.

BACKGROUND AND OBJECTIVE: Fraction of Inspired Oxygen is one of the arbitrary set ventilator parameters which has critical influence on the concentrat...

Neural network and support vector machine for the prediction of chronic kidney disease: A comparative study.

This paper aims to assist in the prevention of Chronic Kidney Disease (CKD) by utilizing machine learning techniques to diagnose CKD at an early stage...

Directional Relationship Between Vitamin D Status and Prediabetes: A New Approach from Artificial Neural Network in a Cohort of Workers with Overweight-Obesity.

Despite the increasing literature on the association of diabetes with inflammation, cardiovascular risk, and vitamin D (25(OH)D) concentrations, stro...

Association of nonalcoholic fatty liver and chronic kidney disease: An analysis of 37,825 cases from health checkup center in Taiwan.

OBJECTIVE: Nonalcoholic fatty liver (NAFLD) and chronic kidney disease (CKD) share common pathogenic mechanisms and risk factors. The relationship bet...

Accuracy of American College of Surgeons National Surgical Quality Improvement Program Universal Surgical Risk Calculator in Predicting Complications Following Robot-Assisted Radical Cystectomy at a National Comprehensive Cancer Center.

There is paucity of literature about the validation of the American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP) sur...

Automated Stoichiometry Analysis of Single-Molecule Fluorescence Imaging Traces via Deep Learning.

The stoichiometry of protein complexes is precisely regulated in cells and is fundamental to protein function. Singe-molecule fluorescence imaging bas...

Specific impact of past and new major cardiovascular events on acute kidney injury and end-stage renal disease risks in diabetes: a dynamic view.

BACKGROUND: Interconnections between major cardiovascular events (MCVEs) and renal events are recognized in diabetes, however, the specific impact of ...

Comparison and development of machine learning tools in the prediction of chronic kidney disease progression.

BACKGROUND: Urinary protein quantification is critical for assessing the severity of chronic kidney disease (CKD). However, the current procedure for ...

A Novel CNN-Based CAD System for Early Assessment of Transplanted Kidney Dysfunction.

This paper introduces a deep-learning based computer-aided diagnostic (CAD) system for the early detection of acute renal transplant rejection. For no...

Generating automated kidney transplant biopsy reports combining molecular measurements with ensembles of machine learning classifiers.

We previously reported a system for assessing rejection in kidney transplant biopsies using microarray-based gene expression data, the Molecular Micro...

An Equation Based on Fuzzy Mathematics to Assess the Timing of Haemodialysis Initiation.

In order to develop an equation that integrates multiple clinical factors including signs and symptoms associated with uraemia to assess the initiatio...

Identifying Factors That Affect Patient Survival After Orthotopic Liver Transplant Using Machine-Learning Techniques.

OBJECTIVES: Survival after liver transplant depends on pretransplant, peritransplant, and posttransplant factors. Identifying effective factors for pa...

Machine learning for the prediction of volume responsiveness in patients with oliguric acute kidney injury in critical care.

BACKGROUND AND OBJECTIVES: Excess fluid balance in acute kidney injury (AKI) may be harmful, and conversely, some patients may respond to fluid challe...

A hybrid neural network model for predicting kidney disease in hypertension patients based on electronic health records.

BACKGROUND: Disease prediction based on Electronic Health Records (EHR) has become one hot research topic in biomedical community. Existing work mainl...

Acute renal failure in systemic sclerosis revealing Goodpasture syndrome: "All that glitters is not scleroderma renal crisis".

The most common cause of acute renal failure in systemic sclerosis patients is scleroderma renal crisis but other etiologies have to be considered suc...

Predicting EGFR mutation status in lung adenocarcinoma on computed tomography image using deep learning.

Epidermal growth factor receptor (EGFR) genotyping is critical for treatment guidelines such as the use of tyrosine kinase inhibitors in lung adenocar...

Comparison between two programs for image analysis, machine learning and subsequent classification.

In the early 1950s, flow cytometry was developed as the first method for automated quantitative cellular analysis. In the early 1990s, the first equip...

Kidney cortex segmentation in 2D CT with U-Nets ensemble aggregation.

PURPOSE: This work presents our contribution to one of the data challenges organized by the French Radiology Society during the Journées Francophones ...