Nephrology

Histopathology Based AI Model Predicts Anti-Angiogenic Therapy Response in Renal Cancer Clinical Trial

Predictive biomarkers of treatment response are lacking for metastatic clear cell renal cell carcinoma (ccRCC), a tumor type that is treated with angiogenesis inhibitors, immune checkpoint inhibitors, mTOR inhibitors and a HIF2 inhibitor. The Angioscore, an RNA-based quantification of angiogenesis, is arguably the best candidate to predict anti-angiogenic (AA) response. However, the clinical ado...

Constructing synthetic datasets with generative artificial intelligence to train large language models to classify acute renal failure from clinical notes.

OBJECTIVES: To compare performances of a classifier that leverages language models when trained on synthetic versus authentic clinical notes.

An interpretable machine learning model to predict off-pump coronary artery bypass grafting-associated acute kidney injury.

BACKGROUND: Off-pump coronary artery bypass grafting-associated acute kidney injury (OPCAB-AKI) is related to 30-day perioperative mortality. Existing...

Deep Learning Assessment of Small Renal Masses at Contrast-enhanced Multiphase CT.

Background Accurate characterization of suspicious small renal masses is crucial for optimized management. Deep learning (DL) algorithms may assist wi...

Patient-Reported Outcomes for Robot-Assisted Laparoscopic Extravascular Renal Vein Stent Placements for Nutcracker Syndrome.

Nutcracker phenomenon is the compression of the left renal vein between the superior mesenteric artery (SMA) and the abdominal aorta. Nutcracker synd...

Robot-assisted laparoscopic surgery for rectal cancer in a patient with a horseshoe kidney: A case report.

A 52-year-old, Japanese man presented to the hospital with a complaint of anal bleeding, and detailed examination resulted in a diagnosis of locally a...

Association Between Acute Kidney Injury and the Trendelenburg Position Angle During Robot-assisted Radical Prostatectomy.

BACKGROUND/AIM: Robot-assisted radical prostatectomy (RARP) has been widely adopted as the standard treatment for localized prostate cancer. RARP is s...

Improving accuracy of vascular access quality classification in hemodialysis patients using deep learning with K highest score feature selection.

OBJECTIVE: To develop and evaluate a novel feature selection technique, using photoplethysmography (PPG) sensors, for enhancing the performance of dee...

Transplant nephropathology: Wherefrom, wherein, and whereto.

Renal pathology is a relatively recent entry in nephrology. While diseases of the kidney are old, their study began in the 19th century with the repor...

Deep learning to assess right ventricular ejection fraction from two-dimensional echocardiograms in precapillary pulmonary hypertension.

BACKGROUND: Precapillary pulmonary hypertension (PH) is characterized by a sustained increase in right ventricular (RV) afterload, impairing systolic ...

D3EGFR: a webserver for deep learning-guided drug sensitivity prediction and drug response information retrieval for EGFR mutation-driven lung cancer.

As key oncogenic drivers in non-small-cell lung cancer (NSCLC), various mutations in the epidermal growth factor receptor (EGFR) with variable drug se...

The dawn of multimodal artificial intelligence in nephrology.

StructuralDPPIV: a novel deep learning model based on atom structure for predicting dipeptidyl peptidase-IV inhibitory peptides.

MOTIVATION: Diabetes is a chronic metabolic disorder that has been a major cause of blindness, kidney failure, heart attacks, stroke, and lower limb a...

Proposal of a standardized training curriculum for open and robot-assisted kidney transplantation.

Standardized training programs for open (OKT) and robot-assisted kidney transplantation (RAKT) remain unmet clinical needs. To fill this gap, we desig...

Artificial intelligence-assisted quantification and assessment of whole slide images for pediatric kidney disease diagnosis.

MOTIVATION: Pediatric kidney disease is a widespread, progressive condition that severely impacts growth and development of children. Chronic kidney d...

The AI Agent in the Room: Informing Objective Decision Making at the Transplant Selection Committee

Transplantation is one of the few areas in medicine where the definitive treatment is rationed. Subjective decision-making pose challenges towards the...

Identification of candidate biomarkers and molecular networks associated with Pulmonary Arterial Hypertension using machine learning and plasma multi-Omics analysis

Pulmonary arterial hypertension (PAH) is a rare but severe and life- threatening condition that primarily affects the pulmonary blood vessels and the ...

Neural Granger Causal Discovery for Derangements in ICU-Acquired Acute Kidney Injury Patients.

Nowadays, healthcare systems increasingly utilize automated surveillance of electronic medical record (EMR) data to detect adverse events with specifi...

Towards Interpretable End-Stage Renal Disease (ESRD) Prediction: Utilizing Administrative Claims Data with Explainable AI Techniques.

This study explores the potential of utilizing administrative claims data, combined with advanced machine learning and deep learning techniques, to pr...

Ontology-based modeling, integration, and analysis of heterogeneous clinical, pathological, and molecular kidney data for precision medicine.

Many data resources generate, process, store, or provide kidney related molecular, pathological, and clinical data. Reference ontologies offer an oppo...