ReviewBiomedicines2024
Artificial Intelligence Reporting Guidelines' Adherence in Nephrology for Improved Research and Clinical Outcomes.
Review in Biomedicines, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
12 citing papers in PubMed, 11 citations in OpenAlex.
- Artificial intelligence in nephrology: predicting CKD progression and personalizing treatment.International urology and nephrology · 2026Review
- The Evolving Role of Artificial Intelligence in Andrological Surgery: Current Landscape and Future Direction.Journal of clinical medicine · 2026Review
- Full title: evaluating AI guidelines in leading family medicine journals: a cross-sectional study.BMC primary care · 2025Article
- Assessing the quality of reporting in artificial intelligence/machine learning research for cardiac amyloidosis.JAMIA open · 2025Article
- Ethical aspects of artificial intelligence: what urologists need to know.Current opinion in urology · 2025Review
- Ethics and Algorithms to Navigate AI's Emerging Role in Organ Transplantation.Journal of clinical medicine · 2025Review
- Effective Integration of Artificial Intelligence and Blockchain Technologies for Empowerment of Drug Discovery and Development.Current drug discovery technologies · 2025Review
- Evaluation of large language model-generated medical information on idiopathic pulmonary fibrosis.Frontiers in artificial intelligence · 2025Article
- Phase-specific kidney graft failure prediction with machine learning model.Frontiers in artificial intelligence · 2025Article
- Artificial Intelligence in Clinical Trials: A Comparative Study With Nephrologists in Prescreening.Kidney international reports · 2025Article
- Improving IVF Utilization with Patient-Centric Artificial Intelligence-Machine Learning (AI/ML): A Retrospective Multicenter Experience.Journal of clinical medicine · 2024Article
- Patient-Centric In Vitro Fertilization Prognostic Counseling Using Machine Learning for the Pragmatist.Seminars in reproductive medicine · 2024Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 3 institutions in 3 countries.
Funding
Abstract
The use of artificial intelligence (AI) in healthcare is transforming a number of medical fields, including nephrology. The integration of various AI techniques in nephrology facilitates the prediction of the early detection, diagnosis, prognosis, and treatment of kidney disease. Nevertheless, recent reports have demonstrated that the majority of published clinical AI studies lack uniform AI reporting standards, which poses significant challenges in interpreting, replicating, and translating the studies into routine clinical use. In response to these issues, worldwide initiatives have created guidelines for publishing AI-related studies that outline the minimal necessary information that researchers should include. By following standardized reporting frameworks, researchers and clinicians can ensure the reproducibility, reliability, and ethical use of AI models. This will ultimately lead to improved research outcomes, enhanced clinical decision-making, and better patient management. This review article highlights the importance of adhering to AI reporting guidelines in medical research, with a focus on nephrology and urology, and clinical practice for advancing the field and optimizing patient care.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.