Nephrology

Assessment and prediction of restless leg syndrome (RLS) in patients with diabetes mellitus type II through artificial intelligence (AI).

This study aimed to diagnose the incidence of restless leg syndrome (RLS) in patients with diabetes ...

[Determination of tranexamic acid in essential cosmetics by pre-column derivatization capillary electrophoresis coupled with electrogenerated chemiluminescence detection].

-Methylation of tranexamic acid yields an unique derivative, which generates strong co-luminescence ...

Next-Generation Radiogenomics Sequencing for Prediction of EGFR and KRAS Mutation Status in NSCLC Patients Using Multimodal Imaging and Machine Learning Algorithms.

PURPOSE: Considerable progress has been made in the assessment and management of non-small cell lung...

Omitting Cortical Renorrhaphy in Robot-Assisted Partial Nephrectomy: Is it Safe? A Single Center Large Case Series.

Preserving renal function after robot-assisted partial nephrectomy (RAPN) is important and influenc...

Artificial neural network and bioavailability of the immunosuppression drug.

PURPOSE OF REVIEW: The success of organ transplant is determined by number of demographic, clinical,...

Artificial intelligence in transplantation (machine-learning classifiers and transplant oncology).

PURPOSE OF REVIEW: To highlight recent efforts in the development and implementation of machine lear...

Machine-learning algorithms for predicting results in liver transplantation: the problem of donor-recipient matching.

PURPOSE OF REVIEW: Classifiers based on artificial intelligence can be useful to solve decision prob...

An Empirical Method of Automatic Pattern Extraction for Clinical Text Classification.

Clinical text classification is an indispensable and extensively studied problem in medical text pro...

Automatic Extraction of Risk Factors for Dialysis Patients from Clinical Notes Using Natural Language Processing Techniques.

Studies have shown that mental health and comorbidities such as dementia, diabetes and cardiovascula...

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.

Applications of machine learning methods in kidney disease: hope or hype?

PURPOSE OF REVIEW: The universal adoption of electronic health records, improvement in technology, a...

Machine Learning and Deep Neural Network Applications in the Thorax: Pulmonary Embolism, Chronic Thromboembolic Pulmonary Hypertension, Aorta, and Chronic Obstructive Pulmonary Disease.

The radiologic community is rapidly integrating a revolution that has not fully entered daily practi...

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...

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...

[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...

Machine learning in nephrology: scratching the surface.

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

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...

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 ...

[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...