Nephrology

A hybrid neural network model for predicting kidney disease in hypertension patients based on electronic health records.

BACKGROUND: Disease prediction based on Electronic Health Records (EHR) has become one hot research ...

Acute renal failure in systemic sclerosis revealing Goodpasture syndrome: "All that glitters is not scleroderma renal crisis".

The most common cause of acute renal failure in systemic sclerosis patients is scleroderma renal cri...

Predicting EGFR mutation status in lung adenocarcinoma on computed tomography image using deep learning.

Epidermal growth factor receptor (EGFR) genotyping is critical for treatment guidelines such as the ...

Comparison between two programs for image analysis, machine learning and subsequent classification.

In the early 1950s, flow cytometry was developed as the first method for automated quantitative cell...

Kidney cortex segmentation in 2D CT with U-Nets ensemble aggregation.

PURPOSE: This work presents our contribution to one of the data challenges organized by the French R...

A Fully Automated System Using A Convolutional Neural Network to Predict Renal Allograft Rejection: Extra-validation with Giga-pixel Immunostained Slides.

Pathologic diagnoses mainly depend on visual scoring by pathologists, a process that can be time-con...

Identifying progressive CKD from healthy population using Bayesian network and artificial intelligence: A worksite-based cohort study.

Identifying progressive early chronic kidney disease (CKD) patients at a health checkup is a good op...

Group Lasso Regularized Deep Learning for Cancer Prognosis from Multi-Omics and Clinical Features.

Accurate prognosis of patients with cancer is important for the stratification of patients, the opti...

Comparison of long-term outcomes of laparoscopic and robot-assisted laparoscopic partial nephrectomy.

In this study, we compared the long-term oncological and functional outcomes of laparoscopic partial...

Gene Expression Classification of Lung Adenocarcinoma into Molecular Subtypes.

As one of the most common malignancies in the world, lung adenocarcinoma (LUAD) is currently difficu...

Measurement of Glomerular Filtration Rate using Quantitative SPECT/CT and Deep-learning-based Kidney Segmentation.

Quantitative SPECT/CT is potentially useful for more accurate and reliable measurement of glomerular...

Metabolomics Analysis in Acute Paraquat Poisoning Patients Based on UPLC-Q-TOF-MS and Machine Learning Approach.

Most paraquat (PQ) poisoned patients died from acute multiple organ failure (MOF) such as lung, kidn...

Understanding of proton induced synaptic behaviors in three-terminal synapse device for neuromorphic systems.

In this study, we investigate a proton-based three-terminal (3-T) synapse device to realize linear w...

Simultaneous spatiotemporal tracking and oxygen sensing of transient implants in vivo using hot-spot MRI and machine learning.

A varying oxygen environment is known to affect cellular function in disease as well as activity of ...

Differentiation of renal angiomyolipoma without visible fat from renal cell carcinoma by machine learning based on whole-tumor computed tomography texture features.

Machine Learning Accurately Predicts Short-Term Outcomes Following Open Reduction and Internal Fixation of Ankle Fractures.

Ankle fractures are common orthopedic injuries with favorable outcomes when managed with open reduct...

Natural language processing of lifestyle modification documentation.

Lifestyle modification, including diet, exercise, and tobacco cessation, is the first-line treatment...

Patient-Level Prediction of Cardio-Cerebrovascular Events in Hypertension Using Nationwide Claims Data.

BACKGROUND: Prevention and management of chronic diseases are the main goals of national health main...

Generative Adversarial Networks for Facilitating Stain-Independent Supervised and Unsupervised Segmentation: A Study on Kidney Histology.

A major challenge in the field of segmentation in digital pathology is given by the high effort for ...

Differentiating kidney stones from phleboliths in unenhanced low-dose computed tomography using radiomics and machine learning.

OBJECTIVES: Distinguishing between kidney stones and phleboliths can constitute a diagnostic challen...

Influence of segmentation margin on machine learning-based high-dimensional quantitative CT texture analysis: a reproducibility study on renal clear cell carcinomas.

OBJECTIVE: To determine the possible influence of segmentation margin on each step (feature reproduc...