AI Medical Compendium Topic

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Kidney

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Assessing donor kidney function: the role of CIRBP in predicting delayed graft function post-transplant.

Frontiers in immunology
INTRODUCTION: Delayed graft function (DGF) shortens the survival time of transplanted kidneys and increases the risk of rejection. Current methods are inadequate in predicting DGF. More precise tools are required to assess kidney suitability for tran...

The effect of renal function on the clinical outcomes and management of patients hospitalized with hyperglycemic crises.

Frontiers in endocrinology
BACKGROUND: The global prevalence of diabetes has been rising rapidly in recent years, leading to an increase in patients experiencing hyperglycemic crises like diabetic ketoacidosis (DKA) and hyperosmolar hyperglycemic state (HHS). Patients with imp...

Identification and validation of key autophagy-related genes in lupus nephritis by bioinformatics and machine learning.

PloS one
INTRODUCTION: Lupus nephritis (LN) is one of the most frequent and serious organic manifestations of systemic lupus erythematosus (SLE). Autophagy, a new form of programmed cell death, has been implicated in a variety of renal diseases, but the relat...

Machine learning-driven Raman spectroscopy: A novel approach to lipid profiling in diabetic kidney disease.

Nanomedicine : nanotechnology, biology, and medicine
Diabetes mellitus is a chronic metabolic disease that increasingly affects people every year. It is known that with its progression and poor management, metabolic changes can lead to organ dysfunctions, including kidneys. The study aimed to combine R...

Dual-Stage AI Model for Enhanced CT Imaging: Precision Segmentation of Kidney and Tumors.

Tomography (Ann Arbor, Mich.)
OBJECTIVES: Accurate kidney and tumor segmentation of computed tomography (CT) scans is vital for diagnosis and treatment, but manual methods are time-consuming and inconsistent, highlighting the value of AI automation. This study develops a fully au...

Challenges in standardizing preimplantation kidney biopsy assessments and the potential of AI-Driven solutions.

Current opinion in nephrology and hypertension
PURPOSE OF REVIEW: This review explores the variability in preimplantation kidney biopsy processing methods, emphasizing their impact on histological interpretation and allocation decisions driven by biopsy findings. With the increasing use of artifi...

Exploring the subtle and novel renal pathological changes in diabetic nephropathy using clustering analysis with deep learning.

Scientific reports
To decrease the number of chronic kidney disease (CKD), early diagnosis of diabetic kidney disease is required. We performed invariant information clustering (IIC)-based clustering on glomerular images obtained from nephrectomized kidneys of patients...

Machine learning selection of basement membrane-associated genes and development of a predictive model for kidney fibrosis.

Scientific reports
This study investigates the role of basement membrane-related genes in kidney fibrosis, a significant factor in the progression of chronic kidney disease that can lead to end-stage renal failure. The authors aim to develop a predictive model using ma...

Key RNA-binding proteins in renal fibrosis: a comprehensive bioinformatics and machine learning framework for diagnostic and therapeutic insights.

Renal failure
BACKGROUND: Renal fibrosis is a critical factor in chronic kidney disease progression, with limited diagnostic and therapeutic options. Emerging evidence suggests RNA-binding proteins (RBPs) are pivotal in regulating cellular mechanisms underlying fi...

Artificial intelligence links CT images to pathologic features and survival outcomes of renal masses.

Nature communications
Treatment decisions for an incidental renal mass are mostly made with pathologic uncertainty. Improving the diagnosis of benign renal masses and distinguishing aggressive cancers from indolent ones is key to better treatment selection. We analyze 132...