Search Results - "Veeramani, Ashwin"

Spinal Cord Stimulation via Percutaneous and Open Implantation: Systematic Review and Meta-Analysis Examining Complication Rates by Blackburn, Amy Z., Chang, Hunter H., DiSilvestro, Kevin, Veeramani, Ashwin, McDonald, Christopher, Zhang, Andrew S., Daniels, Alan

“…Spinal cord stimulation (SCS) has become a successful therapeutic option for combating chronic pain and can be implanted via percutaneous or open…”
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An Artificial Intelligence Approach to Predicting Unplanned Intubation Following Anterior Cervical Discectomy and Fusion by Veeramani, Ashwin, Zhang, Andrew S, Blackburn, Amy Z., Etzel, Christine M., DiSilvestro, Kevin J., McDonald, Christopher L., Daniels, Alan H.

“…Study Design Level III retrospective database study. Objectives The purpose of this study is to determine if machine learning algorithms are effective in…”
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P19. Predicting readmission following fusion for scoliosis in pediatric patients: A machine-learning approach by Daniels, Alan H., Veeramani, Ashwin, Zhang, Andrew

“…Spine fusion surgery is a common treatment for scoliosis in pediatric patients. Hospital readmission within 30-days of surgery is a costly event. While studies…”
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P149. An artificial neural network approach to predicting mortality after emergency spine trauma surgery with near 90% accuracy by Daniels, Alan H., Veeramani, Ashwin, Zhang, Andrew

“…Traumatic spine injury is a complicated injury to treat that carries a high risk of death. Current research has elucidated on patient characteristics that…”
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Total Hip Arthroplasty After Hip Arthroscopy Has Increased Complications and Revision Risk by Lemme, Nicholas J., Veeramani, Ashwin, Yang, Daniel S., Tabaddor, Ramin R., Daniels, Alan H., Cohen, Eric M.

“…There has been an increase in hip arthroscopy (HA) over the last decade. After HA, some patients may ultimately require a total hip arthroplasty (THA)…”
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Predicting Readmission After Anterior, Posterior, and Posterior Interbody Lumbar Spinal Fusion: A Neural Network Machine Learning Approach by Kuris, Eren O., Veeramani, Ashwin, McDonald, Christopher L., DiSilvestro, Kevin J., Zhang, Andrew S., Cohen, Eric M., Daniels, Alan H.

“…Readmission after spine surgery is costly and a relatively common occurrence. Previous research identified several risk factors for readmission; however, the…”
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Supervised Machine Learning for Predicting Length of Stay After Lumbar Arthrodesis: A Comprehensive Artificial Intelligence Approach by Etzel, Christine M., Veeramani, Ashwin, Zhang, Andrew S., McDonald, Christopher L., DiSilvestro, Kevin J., Cohen, Eric M., Daniels, Alan H.

“…Few studies have evaluated the utility of machine learning techniques to predict and classify outcomes, such as length of stay (LOS), for lumbar fusion…”
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Preoperative Resilience and Early Postoperative Outcomes following Lumbar Spinal Fusion by DiSilvestro, Kevin J., Bond, Dale, Alsoof, Daniel, McDonald, Christopher L., Hartnett, Davis A., Hogan, William B., Veeramani, Ashwin, Daniels, Alan H.

“…Previous studies identified a correlation between preoperative resilience scores and patient reported outcome measures in several surgical subspecialities. No…”
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Transforaminal 360° lumbar endoscopic foraminotomy in postfusion patients: technical note and case series by Telfeian, Albert E, Veeramani, Ashwin, Zhang, Andrew S, Quinn, Matthew S, Daniels, Alan H

“…This report describes a minimally invasive lumbar foraminotomy technique that can be applied in patients who underwent complex spine decompression procedures…”
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Machine Learning Prediction of Length of Stay in Adult Spinal Deformity Patients Undergoing Posterior Spine Fusion Surgery by Zhang, Andrew S, Veeramani, Ashwin, Quinn, Matthew S., Alsoof, Daniel, Kuris, Eren O., Daniels, Alan H.

“…(1) Background: Length of stay (LOS) is a commonly reported metric used to assess surgical success, patient outcomes, and economic impact. The focus of this…”
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Predicting Postoperative Mortality After Metastatic Intraspinal Neoplasm Excision: Development of a Machine-Learning Approach by DiSilvestro, Kevin J., Veeramani, Ashwin, McDonald, Christopher L., Zhang, Andrew S., Kuris, Eren O., Durand, Wesley M., Cohen, Eric M., Daniels, Alan H.

“…Mortality following surgical resection of spinal tumors is a devastating outcome. Naïve Bayes machine learning algorithms may be leveraged in surgical planning…”
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