AIMC Topic: Nephrology

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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...

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...

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 ...

Research hotspots and frontiers of machine learning in renal medicine: a bibliometric and visual analysis from 2013 to 2024.

International urology and nephrology
BACKGROUND: The kidney, an essential organ of the human body, can suffer pathological damage that can potentially have serious adverse consequences on the human body and even affect life. Furthermore, the majority of kidney-induced illnesses are freq...

Advances in critical care nephrology through artificial intelligence.

Current opinion in critical care
PURPOSE OF REVIEW: This review explores the transformative advancement, potential application, and impact of artificial intelligence (AI), particularly machine learning (ML) and large language models (LLMs), on critical care nephrology.

Generative AI in Critical Care Nephrology: Applications and Future Prospects.

Blood purification
BACKGROUND: Generative artificial intelligence (AI) is rapidly transforming various aspects of healthcare, including critical care nephrology. Large language models (LLMs), a key technology in generative AI, show promise in enhancing patient care, st...

How artificial intelligence is transforming nephrology.

BMC nephrology
Current research in nephrology is increasingly focused on elucidating the complexity inherent in tightly interwoven molecular systems and their correlation with pathology and related therapeutics, including dialysis and renal transplantation. Rapid a...