Nephrology

[Artificial intelligence in kidney transplant pathology].

BACKGROUND: Artificial intelligence (AI) systems have showed promising results in digital pathology, including digital nephropathology and specifically also kidney transplant pathology.

Machine learning-based integration develops a stress response stated T cell (Tstr)-related score for predicting outcomes in clear cell renal cell carcinoma.

BACKGROUND: Establishment of a reliable prognostic model and identification of novel biomarkers are urgently needed to develop precise therapy strategies for clear cell renal cell carcinoma (ccRCC). Stress response stated T cells (Tstr) are a new T-cell subtype, which are related to poor disease stage and immunotherapy response in various cancers.

Boosting Clear Cell Renal Carcinoma-Specific Drug Discovery Using a Deep Learning Algorithm and Single-Cell Analysis.

Clear cell renal carcinoma (ccRCC), the most common subtype of renal cell carcinoma, has the high heterogeneity of a highly complex tumor microenviron...

Response accuracy of ChatGPT 3.5 Copilot and Gemini in interpreting biochemical laboratory data a pilot study.

With the release of ChatGPT at the end of 2022, a new era of thinking and technology use has begun. Artificial intelligence models (AIs) like Gemini (...

Comment on: "single-port vs multi-port robot-assisted renal surgery: analysis of perioperative outcomes for excision of high and low complexity renal masses".

Novel non-invasive method for urine mapping: Deep-learning-enabled SERS spectroscopy for the rapid differential detection of kidney allograft injury.

The kidney allograft has been under continuous attack from diverse injuries since the very beginning of organ procurement, leading to a gradual declin...

Deep Learning for Automated Measurement of Total Cardiac Volume for Heart Transplantation Size Matching.

Total Cardiac Volume (TCV)-based size matching using Computed Tomography (CT) is a novel technique to compare donor and recipient heart size in pediat...

Prostatic Fossa Pseudoaneurysm After Robot-Assisted Radical Prostatectomy (RARP): A Case Report.

BACKGROUND RARP is an established procedure in treatment of localized prostate cancer. Hemorrhagic complications in the postoperative period are rare,...

Predictive factors of renal function after robot-assisted partial nephrectomy in clinical T1b tumors.

Robot-assisted partial nephrectomy (RAPN) has been shown to be a safe and effective method for treatment of small renal tumors, including clinical T1b...

The ERUS course on robot-assisted kidney transplantation.

PURPOSE: Robot-assisted kidney transplantation (RAKT) is being increasingly performed at selected referral institutions worldwide. Yet, surgical train...

Deceased-Donor Kidney Transplant Outcome Prediction Using Artificial Intelligence to Aid Decision-Making in Kidney Allocation.

In kidney transplantation, pairing recipients with the highest longevity with low-risk allografts to optimize graft-donor survival is a complex challe...

Deep learning-based glomerulus detection and classification with generative morphology augmentation in renal pathology images.

Glomerulus morphology on renal pathology images provides valuable diagnosis and outcome prediction information. To provide better care, an efficient, ...

Machine learning in risk prediction of continuous renal replacement therapy after coronary artery bypass grafting surgery in patients.

OBJECTIVES: This study aimed to develop machine learning models for risk prediction of continuous renal replacement therapy (CRRT) following coronary ...

Prediction of cardiovascular and renal risk among patients with apparent treatment-resistant hypertension in the United States using machine learning methods.

Apparent treatment-resistant hypertension (aTRH), defined as blood pressure (BP) that remains uncontrolled despite unconfirmed concurrent treatment wi...

Deep learning using contrast-enhanced ultrasound images to predict the nuclear grade of clear cell renal cell carcinoma.

PURPOSE: To assess the effectiveness of a deep learning model using contrastenhanced ultrasound (CEUS) images in distinguishing between low-grade (gra...

Predicting hypertension control using machine learning.

Hypertension is a widely prevalent disease and uncontrolled hypertension predisposes affected individuals to severe adverse effects. Though the import...

A machine learning approach to predict daptomycin exposure from two concentrations based on Monte Carlo simulations.

Daptomycin is a concentration-dependent lipopeptide antibiotic for which exposure/effect relationships have been shown. Machine learning (ML) algorith...

Determining steady-state trough range in vancomycin drug dosing using machine learning.

BACKGROUND: Vancomycin is a renally eliminated, nephrotoxic, glycopeptide antibiotic with a narrow therapeutic window, widely used in intensive care u...

Effect of different targets of goal-directed fluid therapy on intraoperative hypotension and fluid infusion in robot-assisted laparoscopic gynecological surgery: a randomized non-inferiority trial.

Carotid corrected flow time (FTc) and tidal volume challenge pulse pressure variation (VtPPV) are useful clinical parameters for assessing volume stat...

Deep learning model to predict lupus nephritis renal flare based on dynamic multivariable time-series data.

OBJECTIVES: To develop an interpretable deep learning model of lupus nephritis (LN) relapse prediction based on dynamic multivariable time-series data...