Nephrology

Machine Learning-Based Ultrasound Radiomics for Evaluating the Function of Transplanted Kidneys.

The aim of the study described here was to investigate the value of different machine learning models based on the clinical and radiomic features of 2-D ultrasound images to evaluate post-transplant renal function (pTRF). We included 233 patients who underwent ultrasound examination after renal transplantation and divided them into the normal pTRF group (group 1) and the abnormal pTRF group (group...

Validation of a Predictive Model for New Baseline Renal Function After Radical Nephrectomy or Robot-Assisted Partial Nephrectomy in Japanese Patients.

The study's aim was to externally validate a new predictive model for the new baseline glomerular filtration rate (NB-GFR) postnephrectomy among Japanese patients. Patients with renal tumors who underwent radical nephrectomy (RN) or robot-assisted laparoscopic partial nephrectomy (PN) at a single Japanese institution during the period 2000-2020 were retrospectively analyzed. The NB-GFR is define...

ScoMorphoFISH: A deep learning enabled toolbox for single-cell single-mRNA quantification and correlative (ultra-)morphometry.

Increasing the information depth of single kidney biopsies can improve diagnostic precision, personalized medicine and accelerate basic kidney researc...

Xprediction: Explainable EGFR-TKIs response prediction based on drug sensitivity specific gene networks.

In recent years, drug sensitivity prediction has garnered a great deal of attention due to the growing interest in precision medicine. Several computa...

Surgical Selection of T1 Stage Renal Tumor Resection Based on Imaging MAP Score under Smart Medical Care.

Smart medical uses the medical information platform and the current technological means to enable the process of sharing information between medical s...

Predicting acute kidney injury following open partial nephrectomy treatment using SAT-pruned explainable machine learning model.

BACKGROUND: One of the most prevalent complications of Partial Nephrectomy (PN) is Acute Kidney Injury (AKI), which could have a negative impact on su...

[Successful laparoscopic robot-assisted surgical treatment of bilateral ureterosciatic hernias (Lindbom's hernia) and pelvic kidney].

Ureterosciaic hernia is a rarely described pathology that represents a diagnostic and therapeutic challenge for the treating physician. In this case r...

Prediction of chronic kidney disease and its progression by artificial intelligence algorithms.

BACKGROUND AND OBJECTIVE: Aim of nephrologists is to delay the outcome and reduce the number of patients undergoing renal failure (RF) by applying pre...

A deep learning-based precision volume calculation approach for kidney and tumor segmentation on computed tomography images.

Previously, doctors interpreted computed tomography (CT) images based on their experience in diagnosing kidney diseases. However, with the rapid incre...

Deep learning kidney segmentation with very limited training data using a cascaded convolution neural network.

BACKGROUND: Deep learning segmentation requires large datasets with ground truth. Image annotation is time consuming and leads to shortages of ground ...

A deep learning-based precision and automatic kidney segmentation system using efficient feature pyramid networks in computed tomography images.

This paper proposes an encoder-decoder architecture for kidney segmentation. A hyperparameter optimization process is implemented, including the devel...

Comparison of Open and Robot-Assisted Kidney Transplantation in terms of Perioperative and Postoperative Outcomes.

BACKGROUND: The gold standard treatment method for end-stage renal disease (ESRD) is renal transplantation (RT). RT can be done with open or minimally...

Molecular Visualization of Early-Stage Acute Kidney Injury with a DNA Framework Nanodevice.

DNA nanomachines with artificial intelligence have attracted great interest, which may open a new era of precision medicine. However, their in vivo be...

Monitoring Approaches for a Pediatric Chronic Kidney Disease Machine Learning Model.

OBJECTIVE: The purpose of this study is to evaluate the ability of three metrics to monitor for a reduction in performance of a chronic kidney disease...

In silico prediction of potential drug-induced nephrotoxicity with machine learning methods.

In recent years, drug-induced nephrotoxicity has been one of the main reasons for the failure of drug development. Early prediction of the nephrotoxic...

Effect of endoscopic urethral procedures applied after robotic radical prostatectomy on urinary incontinence: A prospective cohort pilot study.

OBJECTIVES: The most common complications after radical prostatectomy (RP) are erectile dysfunction (ED) and urinary incontinence (UI). After RP, pati...

Cone-Beam CT-Guided Transarterial Tagging of Endophytic Renal Tumors with Indocyanine Green for Robot-Assisted Partial Nephrectomy.

PURPOSE: To evaluate the safety, efficacy, and clinical impact of preoperative cone-beam computed tomography (CT)-guided selective embolization of end...

Robot-Assisted Mini-Endoscopic Combined Intrarenal Surgery for Complex and Multiple Calculi: What Are the Real Advantages?

To determine the stone-free rates (SFR) with robot-assisted mini-endoscopic combined intrarenal surgery (mini-ECIRS) and evaluate the impact of intra...

Fast environmental sound classification based on resource adaptive convolutional neural network.

Recently, with the construction of smart city, the research on environmental sound classification (ESC) has attracted the attention of academia and in...

Artificial intelligence applications for pre-implantation kidney biopsy pathology practice: a systematic review.

BACKGROUND: Transplant nephropathology is a highly specialized field of pathology comprising both the evaluation of organ donor biopsy for organ alloc...