AI Medical Compendium Topic

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Kidney Diseases

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Artificial intelligence with kidney disease: A scoping review with bibliometric analysis, PRISMA-ScR.

Medicine
BACKGROUND: Artificial intelligence (AI) has had a significant impact on our lives and plays many roles in various fields. By analyzing the past 30 years of AI trends in the field of nephrology, using a bibliography, we wanted to know the areas of in...

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

AJR. American journal of roentgenology
The objective of our study was to systematically review the literature about the application of artificial intelligence (AI) to renal mass characterization with a focus on the methodologic quality items. A systematic literature search was conducted...

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

Nature reviews. Nephrology
An important need exists to better understand and stratify kidney disease according to its underlying pathophysiology in order to develop more precise and effective therapeutic agents. National collaborative efforts such as the Kidney Precision Medic...

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

Clinical journal of the American Society of Nephrology : CJASN
BACKGROUND AND OBJECTIVES: Immunohistopathology is an essential technique in the diagnostic workflow of a kidney biopsy. Deep learning is an effective tool in the elaboration of medical imaging. We wanted to evaluate the role of a convolutional neura...

Robot-assisted laparoscopic unroofing and fulguration of sequestered caliceal diverticula cluster.

Journal of pediatric urology
INTRODUCTION: We report a rare case of four sequestered caliceal diverticula that failed previous percutaneous sclerotherapy and were subsequently managed with robot-assisted laparoscopic unroofing and fulguration of the sequestered diverticula clust...

Identification of glomerular lesions and intrinsic glomerular cell types in kidney diseases via deep learning.

The Journal of pathology
Identification of glomerular lesions and structures is a key point for pathological diagnosis, treatment instructions, and prognosis evaluation in kidney diseases. These time-consuming tasks require a more accurate and reproducible quantitative analy...

Inspection of visible components in urine based on deep learning.

Medical physics
PURPOSE: Urinary particles are particularly important parameters in clinical urinalysis, especially for the diagnosis of nephropathy. Therefore, it is highly important to precisely detect urinary particles in the clinical setting. However, artificial...

Applications of machine learning methods in kidney disease: hope or hype?

Current opinion in nephrology and hypertension
PURPOSE OF REVIEW: The universal adoption of electronic health records, improvement in technology, and the availability of continuous monitoring has generated large quantities of healthcare data. Machine learning is increasingly adopted by nephrology...