MD2 (MD/PhD), Orthopaedics
Icahn School of Medicine at Mount Sinai
BS, Biomedical Engineering Rutgers University
My clinical research interests involve the use of artificial intelligence and machine learning to improve risk prognostication, surgical outcomes, and diagnostics in orthopedic surgery. My basic science interests include the study of musculoskeletal developmental biology and tissue engineering applications.
My future interests include becoming an orthopedic surgeon in an academic institution.
In my free time, you’ll find me hiking or cooking.
- Kim, J.S., Merrill, R.K., Arvind, V., Kaji, D., Pasik, S.D., Nwachukwu, C.C., Vargas, L., Osman, N.S., Oermann, E.K., Caridi, J.M. and Cho, S.K., 2017. Examining the Ability of Artificial Neural Networks Machine Learning Models to Accurately Predict Complications Following Posterior Lumbar Spine Fusion. Spine.
- Arvind, V., Costa, A., Badgeley, M., Cho, S. and Oermann, E., 2017. Wide and deep volumetric residual networks for volumetric image classification. arXiv preprint arXiv:1710.01217.
- Hussain, A.K., Vig, K.S., Cheung, Z.B., Phan, K., Lima, M.C., Kim, J.S., Kaji, D.A., Arvind, V. and Cho, S.K.W., 2017. The Impact of Metastatic Spinal Tumor Location on 30-Day Perioperative Mortality and Morbidity After Surgical Decompression. Spine.
- Arvind, V. and Huang, A.H., 2017. Mechanobiology of limb musculoskeletal development. Annals of the New York Academy of Sciences.
- SL Vega, E Liu, Arvind, J. Bushman, HK Sung, M. Becker, S Lelièvre, J. Kohn, PA Vidi, PV Moghe. “High-content image informatics of the structural nuclear protein NuMA parses trajectories for stem/progenitor cell lineages and oncogenic transformation”. Experimental Cell Research, 10.1016/j.yexcr.2016.12.018 (2016).
- SL Vega, A. Dhaliwal, Arvind, P.J. Patel, N Beijer, J. de Boer, N.S. Murthy, J. Kohn, P.V. Moghe. “Organizational Metrics of Interchromatin Speckle Factor Domains: Integrative Classifier for Stem Cell Adhesion & Lineage Signaling”. Integrative Biology, doi: 10.1039/C4IB00281D (2015).
Podium Presentations/Invited Talks
- Kaji, V. Arvind, J. Kim, J.M. Caridi, S.K. Cho. “Artificial Intelligence (AI) Can Predict Complications Better Than Traditional Statistical Testing Following Fusion for Anterior Lumbar Fusion (ALF)”. Podium presentation at NASS (2017).
- Arvind, D. Kaji , J. Kim, J.M. Caridi, S.K. Cho. “Artificial Intelligence (AI) Can Predict Postoperative Complications Better Than Traditional Statistical Testing Following Anterior Cervical Discectomy and Fusion (ACDF)”. Podium presentation at NASS (2017).
- Kim, V. Arvind, D. Kaji, J.M. Caridi, S.K. Cho. “Intelligently Predicting Surgical Complications In Adult Patients Undergoing Anterior Cervical Discectomy And Fusion (ACDF) Using Machine Learning”. (2017) E-Poster at CSRS.
- K. Hussain, K.S. Vig, D. Kaji, P. Kothari, W. Ranson, S. Jacobs, C.O. Ukogu, J.S. Kim, V. Arvind, S.K. Cho. “Hypoalbuminemia as an Independent Risk Factor for 30-Day Morbidity and Mortality in Cervicothoracic Spinal Tumor Excision”. Poster at Scoliosis Research Society (2017).
- Lee, J. DiCapua, P. Kothari, R. Bronheim, S. Somani, D. Kaji, V. Arvind, S.K. Cho. “Preoperative Risk Factors for Delays to Surgery in Posterior Lumbar Fusion Procedures after Hospital Admission”. Poster at NSQIP conference (2017).
- Somani, N. Lee, R. Bronheim, J. DiCapua, V. Arvind, D. Kaji, D. Leven, S.K. Cho. “Assessing Differences From Surgical Specialty in Anterior Cervical Discectomy with Interbody Fusion”. Poster at NSQIP Conference (2017).
- Kothari, R. Bronheim, J. DiCapua, N. Lee, S. Somani, D. Kaji, V. Arvind, S.K. Cho. “Differences in Patient Characteristics and Operative Outcomes for 22,581 Posterior Lumbar Fusion Surgeries Between Neurosurgeons and Orthopedic Surgeons”. Poster at NSQIP conference (2017).
- Arvind, C. Bigarella, S. Ghaffari. “Acetylation Modulates Foxo3 Activity in Stem and Progenitor Cells”. Poster Presented at Icahn School of Medicine at Mount Sinai, NY, (Aug 8, 2014).
- Qadri, S. Vega, V. Arvind, I. Androulakis, P.V. Moghe. “Integrating High Content Cellular Profiling with Systems Biology”. Poster presented at RESBIO Symposium, NJ, July, (2013).
- Aguilar, S. Vega, Arvind, S. Murthy, P.V. Moghe “Imaging-based method to predict topography-induced osteogenic differentiation”. Poster presented at RiSE Symposium, NJ, July, (2013).
- Arvind, D. Kaji , J. Kim, J.M. Caridi, S.K. Cho. “Artificial Intelligence (AI) Can Predict Postoperative Complications Better Than Traditional Statistical Testing Following Posterior Lumbar Fusion (PLF)”. ePoster with time at NASS (2017).
- Kaji, V. Arvind, J. Kim, J.M. Caridi, S.K. Cho. “Artificial Intelligence (AI) Can Predict Complications Better Than Traditional Statistical Testing Following Posterior Cervical Fusion (PCF)”. ePoster at NASS (2017).
- Arvind, SL Vega, L. McCabe, N.S. Murthy, PV Moghe, J. Kohn. “Modulating stem cell-substrate interactions and differentiation by controlling substrate topography via microphase separation”. Frontiers, doi: 10.3389/conf.FBIOE.2016.01.02444 (2016).
- Dhaliwal, S. Vega, Arvind, M. Brenner, Z. Zhang, Y. Mao, J. Kohn, P.V. Moghe. “Parsing Stem Cell Phenotypes Using High Content Imaging of Mechanotransductive Nuclear Reporters”. Biomedical Engineering Society, San Antonio, TX, (2014).
|2017||Invited reviewer, Global Spine Journal|
|2016||4T32GM007280-40: NIH Medical Scientist Training Awardee – NIH|
|2016||Inducted into the Matthew Leydt Society given to student recognized for being in the top 1-2% of Rutgers graduates – President’s Office of Rutgers University|
|2016||Samuel Welkowitz Award the highest award given for academic excellence in biomedical engineering – Rutgers University Department of Biomedical Engineering|
|2015||Barry M. Goldwater Scholarship given for students pursuing careers in the fields of mathematics, the natural sciences, and engineering, and is the most prestigious undergraduate award given in the sciences – United States Congress|
- English, Tamil