Nephrology

Claims-Based Algorithms for Identifying Patients With Pulmonary Hypertension: A Comparison of Decision Rules and Machine-Learning Approaches.

Background Real-world healthcare data are an important resource for epidemiologic research. However, accurate identification of patient cohorts-a crucial first step underpinning the validity of research results-remains a challenge. We developed and evaluated claims-based case ascertainment algorithms for pulmonary hypertension (PH), comparing conventional decision rules with state-of-the-art machi...

Acute kidney disease and long-term outcomes in critically ill acute kidney injury patients with sepsis: a cohort analysis.

BACKGROUND: Acute kidney injury (AKI) is frequent during hospitalization and may contribute to adverse short- and long-term consequences. Acute kidney disease (AKD) reflects the continuing pathological processes and adverse events developing after AKI. We aimed to evaluate the association of AKD, long-term adverse renal function and mortality in a cohort of patients with sepsis.

Deep learning quantification of percent steatosis in donor liver biopsy frozen sections.

BACKGROUND: Pathologist evaluation of donor liver biopsies provides information for accepting or discarding potential donor livers. Due to the urgent ...

Discovery of Dual FGFR4 and EGFR Inhibitors by Machine Learning and Biological Evaluation.

Kinase inhibitors are widely used in antitumor research, but there are still many problems such as drug resistance and off-target toxicity. A more sui...

Artificial Intelligence in Renal Mass Characterization: A Systematic Review of Methodologic Items Related to Modeling, Performance Evaluation, Clinical Utility, and Transparency.

The objective of our study was to systematically review the literature about the application of artificial intelligence (AI) to renal mass characteri...

Utilizing imbalanced electronic health records to predict acute kidney injury by ensemble learning and time series model.

BACKGROUND: Acute Kidney Injury (AKI) is a shared complication among Intensive Care Unit (ICU), marked by high cost, high morbidity and high mortality...

Increasing tendency of urine protein is a risk factor for rapid eGFR decline in patients with CKD: A machine learning-based prediction model by using a big database.

Artificial intelligence is increasingly being adopted in medical fields to predict various outcomes. In particular, chronic kidney disease (CKD) is pr...

Modelling kidney disease using ontology: insights from the Kidney Precision Medicine Project.

An important need exists to better understand and stratify kidney disease according to its underlying pathophysiology in order to develop more precise...

Evaluation of the Classification Accuracy of the Kidney Biopsy Direct Immunofluorescence through Convolutional Neural Networks.

BACKGROUND AND OBJECTIVES: Immunohistopathology is an essential technique in the diagnostic workflow of a kidney biopsy. Deep learning is an effective...

Incorporation of Urinary Neutrophil Gelatinase-Associated Lipocalin and Computed Tomography Quantification to Predict Acute Kidney Injury and In-Hospital Death in COVID-19 Patients.

BACKGROUND: The prevalence of acute kidney injury (AKI) in COVID-19 patients is high, with poor prognosis. Early identification of COVID-19 patients w...

Machine learning predicts stem cell transplant response in severe scleroderma.

OBJECTIVE: The Scleroderma: Cyclophosphamide or Transplantation (SCOT) trial demonstrated clinical benefit of haematopoietic stem cell transplant (HSC...

Prediction modeling-part 2: using machine learning strategies to improve transplantation outcomes.

Kidney transplant recipients and transplant physicians face important clinical questions where machine learning methods may help improve the decision-...

Reverse pseudohyperkalemia is more than leukocytosis: a retrospective study.

BACKGROUND: Hyperkalemia is a potentially life-threatening electrolyte abnormality that often requires urgent treatment. Clinicians should distinguish...

Effects of canagliflozin on serum potassium in the CANagliflozin cardioVascular Assessment Study (CANVAS) Program.

BACKGROUND: The sodium-glucose cotransporter 2 inhibitor canagliflozin has been shown to reduce the risk of cardiovascular and renal events in patient...

Prognostic importance of Kidney, Heart and Interstitial lung diseases (KHI triad) in PH: A machine learning study.

BACKGROUND: Pulmonary hypertension (PH) is a heterogeneous, severe and progressive disease with an impact on quality of life and life-expectancy despi...

Deep-Learning Generation of Synthetic Intermediate Projections Improves Lu SPECT Images Reconstructed with Sparsely Acquired Projections.

The aims of this study were to decrease the Lu-SPECT acquisition time by reducing the number of projections and to circumvent image degradation by add...

Development of a High-Fidelity Robot-Assisted Kidney Transplant Simulation Platform Using Three-Dimensional Printing and Hydrogel Casting Technologies.

Despite the adoption of robotic donor nephrectomy, the steep learning curve of robotic recipient transplantation has hindered the implementation of a...

Evaluation of Hemodialysis Arteriovenous Bruit by Deep Learning.

Physical findings of auscultation cannot be quantified at the arteriovenous fistula examination site during daily dialysis treatment. Consequently, mi...

Case of slowly progressive type 1 diabetes mellitus with drastically reduced insulin secretory capacity after immune checkpoint inhibitor treatment for advanced renal cell carcinoma.

We encountered a 55-year-old Japanese man with advanced renal cell carcinoma and slowly progressive type 1 diabetes mellitus (SPT1DM), whose insulin s...

An ensemble of deep neural networks for kidney ultrasound image classification.

BACKGROUND AND OBJECTIVE: Chronic kidney disease is a worldwide health issue which includes not only kidney failure but also complications of reduced ...