Nephrology

Artificial intelligence and algorithmic computational pathology: an introduction with renal allograft examples.

Whole slide imaging, which is an important technique in the field of digital pathology, has recently...

Deep learning with a convolutional neural network model to differentiate renal parenchymal tumors: a preliminary study.

PURPOSE: With advancements in medical imaging, more renal tumors are detected early, but it remains ...

Clinical advantages of robot-assisted partial nephrectomy versus laparoscopic partial nephrectomy in terms of global and split renal functions: A propensity score-matched comparative analysis.

OBJECTIVES: To identify predictors of renal function preservation, and to compare the global and spl...

Artificial intelligence prediction model for overall survival of clear cell renal cell carcinoma based on a 21-gene molecular prognostic score system.

We developed and validated a new prognostic model for predicting the overall survival in clear cell ...

Optimizing predictive strategies for acute kidney injury after major vascular surgery.

BACKGROUND: Postoperative acute kidney injury is common after major vascular surgery and is associat...

A review on current advances in machine learning based diabetes prediction.

Diabetes is a metabolic disorder comprising of high glucose level in blood over a prolonged period i...

Biomarker-Based Classification and Localization of Renal Lesions Using Learned Representations of Histology-A Machine Learning Approach to Histopathology.

Several deep learning approaches have been proposed to address the challenges in computational patho...

Evaluation of the Use of Single- and Multi-Magnification Convolutional Neural Networks for the Determination and Quantitation of Lesions in Nonclinical Pathology Studies.

Digital pathology platforms with integrated artificial intelligence have the potential to increase t...

Assessment of Thoracic Pain Using Machine Learning: A Case Study from Baja California, Mexico.

Thoracic pain is a shared symptom among gastrointestinal diseases, muscle pain, emotional disorders,...

Assessment of acute kidney injury risk using a machine-learning guided generalized structural equation model: a cohort study.

BACKGROUND: Acute kidney injury is common in the surgical intensive care unit (ICU). It is associate...

Artificial intelligence supported anemia control system (AISACS) to prevent anemia in maintenance hemodialysis patients.

Anemia, for which erythropoiesis-stimulating agents (ESAs) and iron supplements (ISs) are used as pr...

Early risk assessment for COVID-19 patients from emergency department data using machine learning.

Since its emergence in late 2019, the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) h...

Uncertainty quantification in the radiogenomics modeling of EGFR amplification in glioblastoma.

Radiogenomics uses machine-learning (ML) to directly connect the morphologic and physiological appea...

Deep learning for the classification of medical kidney disease: a pilot study for electron microscopy.

Artificial intelligence (AI) is a new frontier and often enigmatic for medical professionals. Cloud ...

Leveraging Deep Learning to Improve Safety of Outpatient Hemodialysis.

AI applications in renal pathology.

The explosive growth of artificial intelligence (AI) technologies, especially deep learning methods,...

Ensemble machine learning prediction and variable importance analysis of 5-year mortality after cardiac valve and CABG operations.

Despite having a similar post-operative complication profile, cardiac valve operations are associate...

DeepACSON automated segmentation of white matter in 3D electron microscopy.

Tracing the entirety of ultrastructures in large three-dimensional electron microscopy (3D-EM) image...

A low RENAL Nephrometry Score can avoid the need for the intraoperative insertion of a ureteral catheter in robot-assisted partial nephrectomy.

BACKGROUND: Intraoperative urinary collecting system entry (CSE) in robot-assisted partial nephrecto...

Assessing Dry Weight of Hemodialysis Patients via Sparse Laplacian Regularized RVFL Neural Network with L-Norm.

Dry weight is the normal weight of hemodialysis patients after hemodialysis. If the amount of water ...

A U-Net based framework to quantify glomerulosclerosis in digitized PAS and H&E stained human tissues.

Reliable counting of glomeruli and evaluation of glomerulosclerosis in renal specimens are essential...