Nephrology

Risk prediction of diabetic nephropathy using machine learning techniques: A pilot study with secondary data.

AIMS: This research work presented a comparative study of machine learning (ML), including two objectives: (i) determination of the risk factors of diabetic nephropathy (DN) based on principal component analysis (PCA) via different cutoffs; (ii) prediction of DN patients using ML-based techniques.

Machine Learning-Based Radiomics Signatures for EGFR and KRAS Mutations Prediction in Non-Small-Cell Lung Cancer.

Early identification of epidermal growth factor receptor (EGFR) and Kirsten rat sarcoma viral oncogene homolog (KRAS) mutations is crucial for selecting a therapeutic strategy for patients with non-small-cell lung cancer (NSCLC). We proposed a machine learning-based model for feature selection and prediction of EGFR and KRAS mutations in patients with NSCLC by including the least number of the mos...

Machine learning model to predict hypotension after starting continuous renal replacement therapy.

Hypotension after starting continuous renal replacement therapy (CRRT) is associated with worse outcomes compared with normotension, but it is difficu...

Safe Concentration Measurement during Bladder Irrigation Using Artificial Intelligence.

We have developed a sensor for monitoring the hemoglobin (Hb) concentration in the effluent of a continuous bladder irrigation. The Hb concentration m...

Efficient deep learning architecture with dimension-wise pyramid pooling for nuclei segmentation of histopathology images.

Image segmentation remains to be one of the most vital tasks in the area of computer vision and more so in the case of medical image processing. Image...

Single- versus multi-port robotic partial nephrectomy: a comparative analysis of perioperative outcomes and analgesic requirements.

Evidence supporting the safe use of the single-port (SP) robot for partial nephrectomy is scarce. The purpose of this study was to compare perioperati...

Soft robotic constrictor for in vitro modeling of dynamic tissue compression.

Here we present a microengineered soft-robotic in vitro platform developed by integrating a pneumatically regulated novel elastomeric actuator with pr...

Intracorporeal Versus Extracorporeal Robot-assisted Kidney Autotransplantation: Experience of the ERUS RAKT Working Group.

BACKGROUND: Kidney autotransplantation is a useful technique to be reserved for cases in which kidney function is compromised by a complex anatomical ...

Deep learning-based transformation of H&E stained tissues into special stains.

Pathology is practiced by visual inspection of histochemically stained tissue slides. While the hematoxylin and eosin (H&E) stain is most commonly use...

A riddle, wrapped in a mystery, inside an enigma: How semantic black boxes and opaque artificial intelligence confuse medical decision-making.

The use of artificial intelligence (AI) in healthcare comes with opportunities but also numerous challenges. A specific challenge that remains underex...

Machine learning model for early prediction of acute kidney injury (AKI) in pediatric critical care.

BACKGROUND: Acute kidney injury (AKI) in pediatric critical care patients is diagnosed using elevated serum creatinine, which occurs only after kidney...

Real-time prediction of intradialytic relative blood volume: a proof-of-concept for integrated cloud computing infrastructure.

BACKGROUND: Inadequate refilling from extravascular compartments during hemodialysis can lead to intradialytic symptoms, such as hypotension, nausea, ...

Chronic kidney disease diagnosis using decision tree algorithms.

BACKGROUND: Chronic Kidney Disease (CKD), i.e., gradual decrease in the renal function spanning over a duration of several months to years without any...

Resolution-based distillation for efficient histology image classification.

Developing deep learning models to analyze histology images has been computationally challenging, as the massive size of the images causes excessive s...

Robot-Assisted Laparoscopic Retroperitoneal Renal Artery Aneurysm Repair: A Rare Case Report and Literature Review.

INTRODUCTION: The treatment of renal artery aneurysms (RAAs) includes surgical repair and endovascular techniques. Surgical repair is divided into ope...

Cascaded Deep Learning Neural Network for Automated Liver Steatosis Diagnosis Using Ultrasound Images.

Diagnosing liver steatosis is an essential precaution for detecting hepatocirrhosis and liver cancer in the early stages. However, automatic diagnosis...

Surgical outcomes of robot-assisted laparoscopic partial nephrectomy for cystic renal cell carcinoma.

To compare the surgical outcomes of robot-assisted partial nephrectomy (RAPN) between patients with cystic renal cell carcinoma (cRCC) and those with ...

Automated identification of glomeruli and synchronised review of special stains in renal biopsies by machine learning and slide registration: a cross-institutional study.

AIMS: Machine learning in digital pathology can improve efficiency and accuracy via prescreening with automated feature identification. Studies using ...

Machine learning-based prediction of acute kidney injury after nephrectomy in patients with renal cell carcinoma.

The precise prediction of acute kidney injury (AKI) after nephrectomy for renal cell carcinoma (RCC) is an important issue because of its relationship...

A New Clinical Utility for Tubular Markers to Identify Kidney Responders to Saxagliptin Treatment in Adults With Diabetic Nephropathy.

OBJECTIVES: In recent clinical studies, saxagliptin exhibited nephroprotective potential by lowering albuminuria. In this study, we aimed to determine...