Nephrology

Artificial intelligence driven next-generation renal histomorphometry.

PURPOSE OF REVIEW: Successful integration of artificial intelligence into extant clinical workflows ...

Seeing the Forest for the Trees: Random Forest Models for Predicting Survival in Kidney Transplant Recipients.

[Efficacy of Neoadjuvant Endocrine Therapy for Prostate Ductal Carcinoma with Large Multiple Cysts Prior to Robot-Assisted Laparoscopic Radical Prostatectomy].

A 71-year-old man with gross hematuria and urinary retention showed a 7×8 cm polycystic mass compres...

Discriminating malignant and benign clinical T1 renal masses on computed tomography: A pragmatic radiomics and machine learning approach.

The aim of this study was to discriminate malignant and benign clinical T1 renal masses on routinely...

Assessing kidney stone composition using deep learning.

The rise and fall of the model for end-stage liver disease score and the need for an optimized machine learning approach for liver allocation.

PURPOSE OF REVIEW: The Model for End-Stage Liver Disease (MELD) has been used to rank liver transpla...

Machine learning in nephrology: scratching the surface.

Machine learning shows enormous potential in facilitating decision-making regarding kidney diseases....

Wearable health devices and personal area networks: can they improve outcomes in haemodialysis patients?

Digitization of healthcare will be a major innovation driver in the coming decade. Also, enabled by ...

Texture analysis and machine learning algorithms accurately predict histologic grade in small (< 4 cm) clear cell renal cell carcinomas: a pilot study.

PURPOSE: To predict the histologic grade of small clear cell renal cell carcinomas (ccRCCs) using te...

[Prediction of gene mutation in lung cancer based on deep learning and histomorphology analysis].

Lung cancer is a most common malignant tumor of the lung and is the cancer with the highest morbidit...

Deep learning predicts function of live retinal pigment epithelium from quantitative microscopy.

Increases in the number of cell therapies in the preclinical and clinical phases have prompted the n...

Considerations for advancing nephrology research and practice through natural language processing.

Much of medical data is buried in the free text of clinical notes and not captured by structured dat...

[New aspects in the treatment of localized renal cell carcinoma].

BACKGROUND: Localized renal cell carcinoma is increasingly relevant in daily urological practice due...

Artificial intelligence approaches to improve kidney care.

Artificial intelligence is increasingly being used to improve diagnosis and prognostication for acut...

Exciting developments in the field of acute kidney injury.

Adverse drug event rates in pediatric pulmonary hypertension: a comparison of real-world data sources.

OBJECTIVE: Real-world data (RWD) are increasingly used for pharmacoepidemiology and regulatory innov...

[Volume Measurements of Post-transplanted Liver of Pediatric Recipients Using Workstations and Deep Learning].

PURPOSE: The purpose of this study was to propose a method for segmentation and volume measurement o...

Retinopathy Analysis Based on Deep Convolution Neural Network.

At medical checkups or mass screenings, the fundus examination is effective for early detection of s...

Machine Intelligence in Cardiovascular Medicine.

The computer science technology trend called artificial intelligence (AI) is not new. Both machine l...

Editorial Comment: Robotic versus other nephroureterectomy techniques: a systematic review and meta-analysis of over 87,000 cases.

Comparison of semi-automatic and deep learning-based automatic methods for liver segmentation in living liver transplant donors.

PURPOSE: To compare the accuracy and repeatability of emerging machine learning based (i.e. deep) au...