ArticleFrontiers in endocrinology2021
Machine-Learning Prediction of Postoperative Pituitary Hormonal Outcomes in Nonfunctioning Pituitary Adenomas: A Multicenter Study.
Article in Frontiers in endocrinology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 2 of them syntheses that pooled it.
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Who cites it
15 citing papers in PubMed, 2 syntheses or guidelines pooled it, 23 citations in OpenAlex.
- Critical shift phase in deep vein thrombosis development after major sellar region tumor surgeries: a systematic review.Annals of medicine · 2025Pooled it
- Pooled it
- Review
- Article
- Artificial intelligence-driven approaches in pituitary neuroendocrine tumors: integrating endocrine-metabolic profiling for enhanced diagnostics and therapeutics.Frontiers in endocrinology · 2025Review
- An overview of hypopituitarism's causes.Frontiers in endocrinology · 2025Review
- Factors affecting hormonal outcomes in patients undergoing surgery for non-functioning pituitary neuroendocrine tumors: a prospective observational study.Neurosurgical review · 2024Observational
- Reporting of Participants' Sex, Race, Ethnicity, and Socioeconomic Status in Pituitary Surgery Literature.Journal of neurological surgery. Part B, Skull base · 2024Article
- A new model for determining risk of male infertility from serum hormone levels, without semen analysis.Scientific reports · 2024Article
- No unfavorable effects on the menstruation recovery of early postoperative hypoprolactinemia after transsphenoidal surgery in patients with lactotroph pituitary neuroendocrine tumor.BMC research notes · 2024Article
- Artificial Intelligence, Radiomics, and Computational Modeling in Skull Base Surgery.Advances in experimental medicine and biology · 2024Review
- Article
- Machine Learning Models to Forecast Outcomes of Pituitary Surgery: A Systematic Review in Quality of Reporting and Current Evidence.Brain sciences · 2023Review
- Deep-learning-based automatic segmentation and classification for craniopharyngiomas.Frontiers in oncology · 2023Article
- Machine Learning for Outcome Prediction in First-Line Surgery of Prolactinomas.Frontiers in endocrinology · 2022Article
Corrections and comments
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Authors and funding
14 authors at 5 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective: No accurate predictive models were identified for hormonal prognosis in non-functioning pituitary adenoma (NFPA). This study aimed to develop machine learning (ML) models to facilitate the prognostic assessment of pituitary hormonal outcomes after surgery. Methods: A total of 215 male patients with NFPA, who underwent surgery in four medical centers from 2015 to 2021, were retrospectively reviewed. The data were pooled after heterogeneity assessment, and they were randomly divided into training and testing sets (172:43). Six ML models and logistic regression models were developed using six anterior pituitary hormones. Results: Only thyroid-stimulating hormone ( Conclusion: Fluctuation in anterior pituitary hormones varies with increases and decreases because of transsphenoidal surgery. The ML models could accurately predict postoperative pituitary outcomes based on preoperative anterior pituitary hormones in NFPA.
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Registered trials
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