Stanford Neurosurgical
Artificial Intelligence and Machine Learning Laboratory

The safety and efficacy of surgery is our number one priority. As we enter the era of big data, the onus is upon us to utilize what we have learned to improve medical care for future generations. Using novel, cutting edge artificial intelligence and machine learning techniques, our goal is to mine through millions of patient records to predict outcomes following all types of surgery. Imagine a virtual algorithm, that is capable of providing a true estimate of surgical risk, outcome, and efficacy – based specifically on your characteristics. This is the very foundation of precision medicine, and will empower physicians to deliver outstanding care.


The focus of my laboratory is to utilize precision medicine techniques to improve the diagnosis and treatment of neurologic conditions. From traumatic brain injury to spinal scoliosis, the ability to capture detailed data regarding clinical symptoms and treatment outcomes has empowered us to do better for patients. Utilize data to do better for patients, that’s what we do.

Assistant Professor of Neurosurgery at the Stanford University Medical Center


  • Risk Factors for Revision Surgery After Primary Adult Thoracolumbar Deformity Surgery. Clinical spine surgery Varshneya, K., Stienen, M. N., Medress, Z. A., Fatemi, P., Pendharkar, A. V., Ratliff, J. K., Veeravagu, A. 2021


    STUDY DESIGN: This is a retrospective cohort study.OBJECTIVE: The aim was to identify the risk factors for revision surgery within 2 years of patients undergoing primary adult spinal deformity (ASD) surgery.SUMMARY OF BACKGROUND DATA: Previous literature reports estimate 20% of patients undergoing thoracolumbar ASD correction undergo reoperation within 2 years. There is limited published data regarding specific risk factors for reoperation in ASD surgery in the short term and long term.METHODS: The authors queried the MarketScan database in order to identify patients who were diagnosed with a spinal deformity and underwent ASD surgery from 2007 to 2015. Patient-level factors and revision risk were investigated during 2 years after primary ASD surgery. Patients under the age of 18 years and those with any prior history of trauma or tumor were excluded from this study.RESULTS: A total 7422 patients underwent ASD surgery during 2007-2015 in the data set. Revision rates were 13.1% at 90 days, 14.5% at 6 months, 16.7% at 1 year, and 19.3% at 2 years. In multivariate multiple logistic regression analysis, obesity [adjusted odds ratio (OR): 1.58, P<0.001] and tobacco use (adjusted OR: 1.38, P=0.0011) were associated with increased odds of reoperation within 2 years. Patients with a combined anterior-posterior approach had lower odds of reoperation compared with those with posterior only approach (adjusted OR: 0.66, P=0.0117).CONCLUSIONS: Obesity and tobacco are associated with increased odds of revision surgery within 2 years of index ASD surgery. Male sex and combined surgical approach are associated with decreased odds of revision surgery.

    View details for DOI 10.1097/BSD.0000000000001124

    View details for PubMedID 33443943

  • Global adoption of robotic technology into neurosurgical practice and research. Neurosurgical review Stumpo, V., Staartjes, V. E., Klukowska, A. M., Golahmadi, A. K., Gadjradj, P. S., Schroder, M. L., Veeravagu, A., Stienen, M. N., Serra, C., Regli, L. 2020


    Recent technological advancements have led to the development and implementation of robotic surgery in several specialties, including neurosurgery. Our aim was to carry out a worldwide survey among neurosurgeons to assess the adoption of and attitude toward robotic technology in the neurosurgical operating room and to identify factors associated with use of robotic technology. The online survey was made up of nine or ten compulsory questions and was distributed via the European Association of the Neurosurgical Societies (EANS) and the Congress of Neurological Surgeons (CNS) in February and March 2018. From a total of 7280 neurosurgeons who were sent the survey, we received 406 answers, corresponding to a response rate of 5.6%, mostly from Europe and North America. Overall, 197 neurosurgeons (48.5%) reported having used robotic technology in clinical practice. The highest rates of adoption of robotics were observed for Europe (54%) and North America (51%). Apart from geographical region, only age under 30, female gender, and absence of a non-academic setting were significantly associated with clinical use of robotics. The Mazor family (32%) and ROSA (26%) robots were most commonly reported among robot users. Our study provides a worldwide overview of neurosurgical adoption of robotic technology. Almost half of the surveyed neurosurgeons reported having clinical experience with at least one robotic system. Ongoing and future trials should aim to clarify superiority or non-inferiority of neurosurgical robotic applications and balance these potential benefits with considerations on acquisition and maintenance costs.

    View details for DOI 10.1007/s10143-020-01445-6

    View details for PubMedID 33252717

  • Commentary: The Enforceability of Noncompete Clauses in the Medical Profession: A Review by the Workforce Committee and the Medico-legal Committee of the Council of State Neurosurgical Societies. Neurosurgery Veeravagu, A., Medress, Z. A., Ratliff, J. 2020

    View details for DOI 10.1093/neuros/nyaa481

    View details for PubMedID 33231255

  • Medical malpractice in spine surgery: a review NEUROSURGICAL FOCUS Medress, Z. A., Jin, M. C., Feng, A., Varshneya, K., Veeravagu, A. 2020; 49 (5): E16


    Medical malpractice is an important but often underappreciated topic within neurosurgery, particularly for surgeons in the early phases of practice. The practice of spinal neurosurgery involves substantial risk for litigation, as both the natural history of the conditions being treated and the operations being performed almost always carry the risk of permanent damage to the spinal cord or nerve roots, a cardiopulmonary event, death, or other dire outcomes. In this review, the authors discuss important topics related to medical malpractice in spine surgery, including tort reform, trends and frequency of litigation claims in spine surgery, wrong-level and wrong-site surgery, catastrophic outcomes including spinal cord injury and death, and ethical considerations.

    View details for DOI 10.3171/2020.8.FOCUS20602

    View details for Web of Science ID 000585759900016

    View details for PubMedID 33130625

  • Adult spinal deformity surgery: is there a need for a second attending? Response JOURNAL OF NEUROSURGERY-SPINE Medress, Z. A., Khormaee, S., Stienen, M. N., Veeravagu, A., Cheng, I. 2020; 33 (5): 558–59

Our Team

The Stanford Neurosurgical Ariticial Intelligence and Machine Learning Laboratory is led by Dr. Anand Veeravagu, an Assistant Professor of Neurosurgery and Assistant Professor of Orthopedic Surgery, by courtesy, and Director of Minimally Invasive NeuroSpine Surgery at Stanford. Our laboratory team includes neurosurgery residents, clinical instructors, and medical students. 

We're Hiring!

We are currently looking for post-doctoral fellows looking to build their career in health policy research with specific attention to neurologic diseases. To apply, please contact us by email: