AIMC Topic: Nephrology

Clear Filters Showing 1 to 10 of 34 articles

Vibe Coding in nephrology education: clinician-led, AI-assisted development of open-source interactive learning tools.

Renal failure
Medical education increasingly incorporates digital technologies; however, many tools remain passive and text-based. is a clinician-led design framework that embeds expert reasoning and the cognitive 'feel' of clinical decision-making into interacti...

Large language models in nephrology: applications and challenges in chronic kidney disease management.

Renal failure
Large language models (LLMs) represent a transformative advance in artificial intelligence, with growing potential to impact chronic kidney disease (CKD) management. CKD is a complex, highly prevalent condition requiring multifaceted care and substan...

A practical guide for nephrologist peer reviewers: evaluating artificial intelligence and machine learning research in nephrology.

Renal failure
Artificial intelligence (AI) and machine learning (ML) are transforming nephrology by enhancing diagnosis, risk prediction, and treatment optimization for conditions such as acute kidney injury (AKI) and chronic kidney disease (CKD). AI-driven models...

Artificial intelligence and perspective for rare genetic kidney diseases.

Kidney international
The integration of big data and artificial intelligence (AI) has revolutionized biomedicine, enhancing our understanding of diseases and health care practices. Although AI has shown remarkable success in some medical fields, its application in nephro...

Imaging and spatially resolved mass spectrometry applications in nephrology.

Nature reviews. Nephrology
The application of spatially resolved mass spectrometry (MS) and MS imaging approaches for studying biomolecular processes in the kidney is rapidly growing. These powerful methods, which enable label-free and multiplexed detection of many molecular c...

A new era in nephrology: the role of super-resolution microscopy in research, medical diagnostic, and drug discovery.

Kidney international
For decades, electron microscopy has been the primary method to visualize ultrastructural details of the kidney, including podocyte foot processes and the slit diaphragm. Despite its status as the gold standard, electron microscopy has significant li...

Assessing the performance of large language models (GPT-3.5 and GPT-4) and accurate clinical information for pediatric nephrology.

Pediatric nephrology (Berlin, Germany)
BACKGROUND: Artificial intelligence (AI) has emerged as a transformative tool in healthcare, offering significant advancements in providing accurate clinical information. However, the performance and applicability of AI models in specialized fields s...

Evaluating AI performance in nephrology triage and subspecialty referrals.

Scientific reports
Artificial intelligence (AI) has shown promise in revolutionizing medical triage, particularly in the context of the rising prevalence of kidney-related conditions with the aging global population. This study evaluates the utility of ChatGPT, a large...

Improving search strategies in bibliometric studies on machine learning in renal medicine.

International urology and nephrology
This paper evaluated the bibliometric study by Li et al. (Int Urol Nephrol, 2024) on machine learning in renal medicine. Although the study claims to summarize the forefront trends and hotspots in this field, several key issues require further clarif...

How to incorporate generative artificial intelligence in nephrology fellowship education.

Journal of nephrology
Traditional nephrology education faces challenges due to expanding medical knowledge, case complexity, and personalized learning needs. Generative artificial intelligence (AI), like ChatGPT, offers potential solutions to enhance nephrology education ...