ReviewJournal of diabetes and metabolic disorders2022
Artificial intelligence perspective in the future of endocrine diseases.
Review in Journal of diabetes and metabolic disorders, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 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
6 citing papers in PubMed.
- Global Research Trends in Artificial Intelligence and Type 2 Diabetes Mellitus: A Bibliometric Perspective.Cureus · 2025Review
- Artificial intelligence is going to transform the field of endocrinology: an overview.Frontiers in endocrinology · 2025Article
- Unveiling diabetes onset: Optimized XGBoost with Bayesian optimization for enhanced prediction.PloS one · 2025Article
- Artificial Intelligence (AI) and Internet of Medical Things (IoMT) Assisted Biomedical Systems for Intelligent Healthcare.Biosensors · 2022Review
- Elevated All-Cause Mortality among Overweight Older People: AI Predicts a High Normal Weight Is Optimal.Geriatrics (Basel, Switzerland) · 2022Article
- A Glimpse into the Realm that Combines Artificial Intelligence and Endocrinology.Indian journal of endocrinology and metabolismReview
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In recent years, artificial intelligence (AI) shows promising results in the diagnosis, prediction, and management of diseases. The move from handwritten medical notes to electronic health records and a huge number of digital data commenced in the era of big data in medicine. AI can improve physician performance and help better clinical decision making which is called augmented intelligence. The methods applied in the research of AI and endocrinology include machine learning, artificial neural networks, and natural language processing. Current research in AI technology is making major efforts to improve decision support systems for patient use. One of the best-known applications of AI in endocrinology was seen in diabetes management, which includes prediction, diagnosis of diabetes complications (measuring microalbuminuria, retinopathy), and glycemic control. AI-related technologies are being found to assist in the diagnosis of other endocrine diseases such as thyroid cancer and osteoporosis. This review attempts to provide insight for the development of prospective for AI with a focus on endocrinology.
Indexed as
Identifiers
What Socratic 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 Socratic graph.