Research graph
References from Clinically informed preoperative risk stratification for MRI-defined non gross-total resection in nonfunctioning pituitary neuroendocrine tumors: a single-center internal validation study. Local targets link to admitted publications; unresolved targets remain external evidence.
Radiomics in pituitary adenomas: a systematic review of clinical applications and predictive models
10.3390/jcm14186595 · 2025 · External reference
Overview of the 2022 WHO classification of pituitary tumors
10.1007/s12022-022-09703-7 · 2022 · External reference
The HACKD score-predicting extent of resection of pituitary macroadenomas through an endoscopic endonasal transsphenoidal approach
10.1227/ons.0000000000000488 · 2022 · External reference
Preoperative assessment of tumor consistency and gross total resection in pituitary adenoma: radiomic analysis of T2-weighted MRI and interpretation of contributing radiomic features
10.1016/j.bas.2025.104237 · 2025 · External reference
TRIPOD+AI statement: updated guidance for reporting clinical prediction models that use regression or machine learning methods
10.1136/bmj-2023-078378 · 2024 · External reference
Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD): the TRIPOD statement
10.1016/j.jclinepi.2014.11.010 · 2015 · External reference
Fully automated grading of pituitary adenoma
10.1016/j.ynirp.2025.100233 · 2025 · External reference
Non-functioning pituitary adenomas: indications for pituitary surgery and post-surgical management
10.1007/s11102-019-00960-0 · 2019 · External reference
Reappraising prediction of surgical complexity of non-functioning pituitary adenomas after transsphenoidal surgery: the modified TRANSSPHER grade
10.1007/s11102-024-01495-9 · 2025 · External reference
Long-term outcomes after endoscopic endonasal surgery for nonfunctioning pituitary macroadenomas
10.3171/2019.11.jns192457 · 2021 · External reference
Improving the radiological prediction of surgical resection of non-functioning pituitary adenomas
10.1007/s40618-024-02479-z · 2025 · External reference
Machine learning-based models for preoperative prediction of pituitary adenoma consistency: a systematic review and meta-analysis
10.1007/s00701-026-06775-w · 2026 · External reference
A machine learning approach to predict early outcomes after pituitary adenoma surgery
10.3171/2018.8.focus18268 · 2018 · External reference
Clinicopathological features and outcomes in non-functioning pituitary neuroendocrine tumors: a transcription factor-driven subtype analysis
10.1007/s11060-025-05418-x · 2026 · External reference
Endoscopic endonasal transsphenoidal approach to large and giant pituitary adenomas: institutional experience and predictors of extent of resection: clinical article
10.3171/2014.3.jns131679 · 2014 · External reference
Residual tumor confers a 10-fold increased risk of regrowth in clinically nonfunctioning pituitary tumors
10.1210/js.2019-00163 · 2019 · External reference
Predictive model of resection in endoscopic endonasal approach for pituitary adenomas based on anatomical limits
10.1016/j.neucie.2022.11.010 · 2023 · External reference
Using machine learning to predict remission after surgery for pituitary adenoma: a systematic review and meta-analysis
10.1007/s12020-025-04351-3 · 2025 · External reference
Validation of the TRANSSPHER study: a multicenter predictive scoring tool for extent of resection in pituitary adenoma surgery
10.1093/ons/opy386 · 2019 · External reference
PROBAST+AI: an updated quality, risk of bias, and applicability assessment tool for prediction models using regression or artificial intelligence methods
10.1136/bmj-2024-082505 · 2025 · External reference
Predicting resection success in giant pituitary adenomas: morphologic determinants and a preoperative multivariate model
10.3389/fendo.2026.1759071 · 2026 · External reference
Predictive modeling of nonfunctioning giant pituitary neuroendocrine tumor resection: a multi-planar perspective
10.1016/j.wneu.2024.123653 · 2025 · External reference
Regression modeling with convolutional neural network for predicting extent of resection from preoperative MRI in giant pituitary adenomas: a pilot study
10.3171/2024.10.jns241527 · 2025 · External reference
Volumetric study of nonfunctioning pituitary adenomas: predictors of gross total resection
10.1016/j.wneu.2020.12.020 · 2021 · External reference
Machine learning models to forecast outcomes of pituitary surgery: a systematic review in quality of reporting and current evidence
10.3390/brainsci13030495 · 2023 · External reference
Adaptive evaluation of gross total resection rates for endoscopic endonasal approach based on preoperative MRI morphological features of pituitary adenomas
10.3389/fonc.2024.1481899 · 2024 · External reference
Utility of deep neural networks in predicting gross-total resection after transsphenoidal surgery for pituitary adenoma: a pilot study
10.3171/2018.8.focus18243 · 2018 · External reference
Multicenter external validation of the Zurich Pituitary Score
10.1007/s00701-020-04286-w · 2020 · External reference
Calibration: the Achilles heel of predictive analytics
10.1186/s12916-019-1466-7 · 2019 · External reference
A calibration hierarchy for risk models was defined: from utopia to empirical data
10.1016/j.jclinepi.2015.12.005 · 2016 · External reference
Decision curve analysis: a novel method for evaluating prediction models
10.1177/0272989x06295361 · 2006 · External reference
Development and external validation of clinical prediction models for pituitary surgery
10.1016/j.bas.2023.102668 · 2023 · External reference
