ReviewHormone research in paediatrics2025
EndoCompass Project: Artificial Intelligence in Endocrinology.
Review in Hormone research in paediatrics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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
1 citing paper in PubMed.
- Acromegaly diagnosis.The Journal of clinical endocrinology and metabolism · 2026Review
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.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundEndocrine science remains underrepresented in European Union research programs despite the fundamental role of hormone health in human wellbeing. Analysis of the CORDIS database reveals a persistent gap between the societal impact of endocrine disorders and their research prioritization. At national funding level, endocrine societies report limited or little attention of national research funding towards endocrinology. The EndoCompass project - a joint initiative between the European Society of Endocrinology and the European Society of Paediatric Endocrinology, aimed to identify and promote strategic research priorities in endocrine science to address critical hormone-related health challenges.
methodsResearch priorities were established through comprehensive analysis of the EU CORDIS database covering the Horizon 2020 framework period (2014-2020). Expert analysis examined the current landscape of artificial intelligence (AI) applications in endocrinology, focussing on data-sharing frameworks, fairness considerations, and training needs.
resultsResearch priorities encompass 3 domains: establishing compliant frameworks for clinical and omic data sharing in endocrinology; developing fair and unbiased AI systems that account for demographic and clinical diversity while preventing physician de-skilling; and creating comprehensive AI training programs for endocrinologists at all career stages. Special emphasis is placed on coordinating AI initiatives across medical specialities while maintaining endocrine-specific requirements.
conclusionsThis component of the EndoCompass project provides an evidence-based roadmap for integrating AI into endocrine practice and research. The analysis demonstrates the need for balanced approaches that leverage AI capabilities while preserving clinical expertise. The findings support strategic investment in AI infrastructure, training, and fairness-aware system development.
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.