Publications and Projects

Current Projects

  • Automated intraoperative anatomical structure recognition
  • Fast CT to MRI synthesis in the lumbar spine
  • Prediction of surgical outcome after microsurgery for unruptured intracranial aneurysms
  • Predictive analytics in pituitary surgery
  • Low-level entry course on machine learning-based predictive analytics for clinicians


Staartjes VE, Stumpo V, Kernbach JM, Klukowska AM, Gadjradj PS, Schröder ML, Veeravagu A, Stienen MN, van Niftrik CHB, Serra C, Regli L (2020) Machine learning in neurosurgery: a global survey. Acta Neurochirurgica
doi: 10.1007/s00701-020-04532-1

Kernbach JM, Staartjes VE (2020) Predicted Prognosis of Pancreatic Cancer Patients by Machine Learning-Letter. Clinical Cancer Research 15;26(14):3891
doi: 10.1158/1078-0432.CCR-20-0523

Staartjes VE, Kernbach JM (2020) Significance of external validation in clinical machine learning: let loose too early?. The Spine Journal 20(7):1159-1160
doi: 10.1016/j.spinee.2020.02.016

Staartjes VE, Kernbach JM (2020) Machine learning-based clinical prediction modeling — A practical guide for clinicians. arXiv [Preprint]
doi: arXiv:2006.15069

Staartjes VE, Broggi M, Zattra CM, Vasella F, Velz J, Schiavolin S, Serra C, Bartek J, Fletcher-Sandersjöö A, Förander P, Kalasauskas D, Renovanz M, Ringel F, Brawanski KR, Kerschbaumer J, Freyschlag CF, Jakola AS, Sjåvik K, Solheim O, Schatlo B, Sachkova A, Bock HC, Hussein A, Rohde V, Broekman MLD, Nogarede CO, Lemmens CMC, Kernbach JM, Neuloh G, Bozinov O, Krayenbühl N, Sarnthein J, Ferroli P, Regli L, Stienen MN (2020) Development and external validation of a clinical prediction model for functional impairment after intracranial tumor surgery. Journal of Neurosurgery 1, 1–8.
doi: 10.3171/2020.4.JNS20643

Zoli M, Staartjes VE, Guaraldi F, Friso F, Rustici A, Asioli S, Sollini G, Pasquini E, Regli L, Serra C, Mazzatenta D (2020) Machine learning-based prediction of outcomes of the endoscopic endonasal approach in Cushing disease: is the future coming?. Neurosurgical Focus 48(6):E5.
doi: 10.3171/2020.3.FOCUS2060

Voglis S, van Niftrik CHB, Staartjes VE, Brandi G, Tschopp O, Regli L, Serra C (2020) Feasibility of machine learning based predictive modelling of postoperative hyponatremia after pituitary surgery. Pituitary
doi: 10.1007/s11102-020-01056-w

Staartjes VE, Kernbach JM (2020) Letter to the Editor Regarding “Investigating Risk Factors and Predicting Complications in Deep Brain Stimulation Surgery with Machine Learning Algorithms”World Neurosurgery 137:496.
doi: 10.1016/j.wneu.2020.01.189

Staartjes VE, Sebök M, Blum PG, Serra C, Germans MR, Krayenbühl N, Regli L, Esposito G. (2020) Development of machine learning-based preoperative predictive analytics for unruptured intracranial aneurysm surgery: a pilot study. Acta Neurochirurgica.
doi: 10.1007/s00701-020-04355-0

Staartjes VE, Kernbach JM (2020) Importance of calibration assessment in machine learning-based predictive analytics. J Neurosurg Spine 1‐2.
doi: 10.3171/2019.12.SPINE191503

Staartjes VE, Stienen MN (2019) Data Mining in Spine Surgery: Leveraging Electronic Health Records for Machine Learning and Clinical Research. Neurospine 16 (4), 654-656.
doi: 10.14245/ns.1938434.217

Quddusi A, Eversdijk HAJ, Klukowska AM, de Wispelaere MP, Kernbach JM, Schröder ML, Staartjes VE (2019) External validation of a prediction model for pain and functional outcome after elective lumbar spinal fusion. European Spine Journal
doi: 10.1007/s00586-019-06189-6

Staartjes VE, Zattra CM, Akeret K, Maldaner N, Muscas G, Bas van Niftrik CH, Fierstra J, Regli L, Serra C (2019) Neural network-based identification of patients at high risk for intraoperative cerebrospinal fluid leaks in endoscopic pituitary surgery. Journal of Neurosurgery 1–7.
doi: 10.3171/2019.4.JNS19477

van Niftrik CHB, van der Wouden F, Staartjes VE, Fierstra J, Stienen MN, Akeret K, Sebök M, Fedele T, Sarnthein J, Bozinov O, Krayenbühl N, Regli L, Serra C (2019) Machine Learning Algorithm Identifies Patients at High Risk for Early Complications After Intracranial Tumor Surgery: Registry-Based Cohort Study. Neurosurgery
doi: 10.1093/neuros/nyz145

Siccoli A, de Wispelaere MP, Schröder ML, Staartjes VE (2019) Machine learning-based preoperative predictive analytics for lumbar spinal stenosis. Neurosurgical Focus 46:E5.
doi: 10.3171/2019.2.FOCUS18723

Staartjes VE, de Wispelaere MP, Vandertop WP, Schröder ML (2019) Deep learning-based preoperative predictive analytics for patient-reported outcomes following lumbar discectomy: feasibility of center-specific modeling. The Spine Journal 19:853–861.
doi: 10.1016/j.spinee.2018.11.009

Staartjes VE, Serra C, Muscas G, Maldaner N, Akeret K, van Niftrik CHB, Fierstra J, Holzmann D, Regli L (2018) Utility of deep neural networks in predicting gross-total resection after transsphenoidal surgery for pituitary adenoma: a pilot study. Neurosurgical Focus 45:E12.
doi: 10.3171/2018.8.FOCUS18243

Staartjes VE, Schröder ML (2018) Class imbalance in machine learning for neurosurgical outcome prediction: are our models valid? Journal of Neurosurgery: Spine 29:611–612.
doi: 10.3171/2018.5.SPINE18543