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.

Research

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

Publications

  • Factors which predict adverse events following surgery in adults with cervical spinal deformity BONE & JOINT JOURNAL Varshneya, K., Jokhai, R., Medress, Z. A., Stienen, M. N., Ho, A., Fatemi, P., Ratliff, J. K., Veeravagu, A. 2021; 103B (4): 734–38
  • Factors which predict adverse events following surgery in adults with cervical spinal deformity. The bone & joint journal Varshneya, K., Jokhai, R., Medress, Z. A., Stienen, M. N., Ho, A., Fatemi, P., Ratliff, J. K., Veeravagu, A. 2021; 103-B (4): 734–38

    Abstract

    AIMS: The aim of this study was to identify the risk factors for adverse events following the surgical correction of cervical spinal deformities in adults.METHODS: We identified adult patients who underwent corrective cervical spinal surgery between 1 January 2007 and 31 December 2015 from the MarketScan database. The baseline comorbidities and characteristics of the operation were recorded. Adverse events were defined as the development of a complication, an unanticipated deleterious postoperative event, or further surgery. Patients aged < 18 years and those with a previous history of tumour or trauma were excluded from the study.RESULTS: A total of 13,549 adults in the database underwent primary corrective surgery for a cervical spinal deformity during the study period. A total of 3,785 (27.9%) had a complication within 90 days of the procedure, and 3,893 (28.7%) required further surgery within two years. In multivariate analysis, male sex (odds ratio (OR) 0.90 (95% confidence interval (CI) 0.8 to 0.9); p = 0.019) and a posterior approach (compared with a combined surgical approach, OR 0.66 (95% CI 0.5 to 0.8); p < 0.001) significantly decreased the risk of complications. Osteoporosis (OR 1.41 (95% CI 1.3 to 1.6); p < 0.001), dyspnoea (OR 1.48 (95% CI 1.3 to 1.6); p < 0.001), cerebrovascular accident (OR 1.81 (95% CI 1.6 to 2.0); p < 0.001), a posterior approach (compared with an anterior approach, OR 1.23 (95% CI 1.1 to 1.4); p < 0.001), and the use of bone morphogenic protein (BMP) (OR 1.22 (95% CI 1.1 to 1.4); p = 0.003) significantly increased the risks of 90-day complications. In multivariate regression analysis, preoperative dyspnoea (OR 1.50 (95% CI 1.3 to 1.7); p < 0.001), a posterior approach (compared with an anterior approach, OR 2.80 (95% CI 2.4 to 3.2; p < 0.001), and postoperative dysphagia (OR 2.50 (95% CI 1.8 to 3.4); p < 0.001) were associated with a significantly increased risk of further surgery two years postoperatively. A posterior approach (compared with a combined approach, OR 0.32 (95% CI 0.3 to 0.4); p < 0.001), the use of BMP (OR 0.48 (95% CI 0.4 to 0.5); p < 0.001) were associated with a significantly decreased risk of further surgery at this time.CONCLUSION: The surgical approach and intraoperative use of BMP strongly influence the risk of further surgery, whereas the comorbidity burden and the characteristics of the operation influence the rates of early complications in adult patients undergoing corrective cervical spinal surgery. These data may aid surgeons in patient selection and surgical planning. Cite this article: Bone Joint J2021;103-B(4):734-738.

    View details for DOI 10.1302/0301-620X.103B4.BJJ-2020-0845.R2

    View details for PubMedID 33789479

  • 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

    Abstract

    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

    Abstract

    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


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: neurobigdata@stanford.edu