Nephrology

Glo-In-One-v2: holistic identification of glomerular cells, tissues, and lesions in human and mouse histopathology.

PURPOSE: Segmenting intraglomerular tissue and glomerular lesions traditionally depends on detailed ...

Sequence-based virtual screening using transformers.

Protein-ligand interactions play central roles in myriad biological processes and are of key importa...

PDSNet: Patient-Disease Dual Spatial Similarity Neural Networks for Predicting Heart Failure Risk Using Short Electronic Health Records.

Heart failure (HF) is a complex and heterogeneous syndrome caused by diverse factors, such as atrial...

Machine learning and transcriptomics in the research on biomarkers of chronic kidney disease: technical robustness, clinical feasibility and ethical standards.

Advancements in lung cancer: molecular insights, innovative therapies, and future prospects.

Still among the most common and deadly cancers worldwide, lung cancer causes major morbidity and dea...

Development and validation of machine learning predictive models for assessing dialysis adequacy in dialysis patients.

PURPOSE: The assessment of dialysis adequacy is of great clinical importance. However, it depends on...

Neural network-based identification for scallops (Pecten maximus) in natural marine habitats.

The Great Atlantic scallop, or King scallop (Pecten maximus), ranks third in value after mackerel an...

Differential effects of demographics and risk factors on the nonlinear orthotropic mechanical properties of human femoropopliteal arteries.

Understanding how demographics and risk factors differentially affect the nonlinear orthotropic mech...

Machine Learning-Driven Prediction of Electrochemical Promotion in the Reverse Water Gas Shift Reaction.

Electrochemical promotion of catalysis (EPOC) provides an effective and versatile strategy to enhanc...

Comments on "deep learning for kidney trauma detection: CT image algorithm performance and external validation. - experimental study".

Preparing clinical research data for artificial intelligence readiness: insights from the National Institute of Diabetes and Digestive and Kidney Diseases data centric challenge.

OBJECTIVES: The success of artificial intelligence (AI) and machine learning (ML) approaches in biom...

Exploring the comorbidity mechanisms of ITGB2 in rheumatoid arthritis and membranous nephropathy through integrated bioinformatics analysis.

BACKGROUND: Patients with rheumatoid arthritis (RA) are more likely to comorbid renal diseases, with...

Clinical diagnostic and prognostic value of homocysteine combined with hemoglobin [f (Hcy-Hb)] in cardio-renal syndrome caused by primary acute myocardial infarction.

BACKGROUND: Cardio-renal syndrome (CRS), characterized by multi-organ interaction, is frequently ove...

Development and validation of risk prediction models for acute kidney disease in gout patients: a retrospective study using machine learning.

BACKGROUND: Limited research has been conducted on the prevalence of acute kidney injury (AKI) and a...

Machine learning based prediction of MnO cathode discharge capacity for high-performance zinc-ion batteries.

Zinc-ion batteries (ZIBs) are considered as a cheaper, non-toxic and safer alternative to lithium-io...

Comment on "Artificial Intelligence-based multi-modal prediction for nuclear grading status and prognosis of clear cell renal cell carcinoma: a multicenter cohort study".

Clinical characteristics and CKD care delivery in African American and American Indian or Alaska Native patients: A real-world cohort study.

BACKGROUND: Racially minoritized populations in the United States (US), notably African American (AA...

Ultra-low dose imaging in a standard axial field-of-view PET.

Though ultra-low dose (ULD) imaging offers notable benefits, its widespread clinical adoption faces ...

Identification of podocyte molecular markers in diabetic kidney disease via single-cell RNA sequencing and machine learning.

Diabetic kidney disease (DKD) is a major cause of end-stage renal disease globally, with podocytes b...

Computer vision to predict cell seeding coverage in re-endothelialized mouse lungs.

Transplantation of donor grafts recellularized with recipient-derived or non-immunogenic universal c...

2.5D Deep Learning-Based Prediction of Pathological Grading of Clear Cell Renal Cell Carcinoma Using Contrast-Enhanced CT: A Multicenter Study.

RATIONALE AND OBJECTIVES: To develop and validate a deep learning model based on arterial phase-enha...