Posts by Collection

Development of a Practical Arthritic Grip for Common Use

Our project began as an investigation of difficulties that osteoarthritic patients may have in their daily lives and current solutions that attempt to solve those problems. We focused mainly on osteoarthritis (OA) in hands due to its prevalence in the elderly population. After several prototype iterations, we came up with a final design that greatly reduced to force needed to insert kitchen utensils and increased the number of compatible utensils.

Deriving Actionable Strategies Using Machine Learning and Correlation Analysis

Our goal with this project was to figure out how CarMax could best tailor it’s marketing & inventory strategies to draw in distinct segments of customers. We proposed the development of the Oracle User Interface Tool, which would provide a personalized experience for CarMax users. Our proposal won 1st place at the CarMax Analytics Competition.

Novel Surgical Training Simulator for Lateral Access Spine Surgery

We built a training model for Mayo Clinic resident neurosurgeons to use when learning the the lateral access lumbar fusion (LLIF) procedure.

Addressing Inequities in Academic Recognition Standards for Disadvantaged Groups at the Georgia Institute of Technology

We submitted a proposal to Georgia Tech’s Student Innovation Competition – Promoting Equity and Access which was further reviewed by the Georgia State Board in Fall of 2022 for implementation.

A Novel Three-Pronged Framework to Increase Blood Donations in the 21st Century

Our team submitted a proposal to the Dept. of Health and Human Services on increasing blood donations with novel technologies.

Machine learning for prospective identification of immunotherapy related adverse events (irAEs)

Published in 2020 ASCO Annual Meeting, 2020

Citation: Margalski, Daniel, et al. “Machine Learning for Prospective Identification of Immunotherapy Related Adverse Events (Iraes).” Journal of Clinical Oncology, vol. 38, no. 15_suppl, 2020, https://doi.org/10.1200/jco.2020.38.15_suppl.e14064.

Extracting smoking status from electronic health records using NLP and deep learning

Published in AMIA Summits on Translational Science Proceedings, 2020

Citation: Rajendran S, Topaloglu U. Extracting Smoking Status from Electronic Health Records Using NLP and Deep Learning. AMIA Jt Summits Transl Sci Proc. 2020 May 30;2020:507-516. PMID: 32477672; PMCID: PMC7233082.

Cloud-Based Federated Learning Implementation Across Medical Centers

Published in JCO Clinical Cancer Informatics, 2021

Citation: Rajendran S, Obeid JS, Binol H, D Agostino R Jr, Foley K, Zhang W, Austin P, Brakefield J, Gurcan MN, Topaloglu U. Cloud-Based Federated Learning Implementation Across Medical Centers. JCO Clin Cancer Inform. 2021 Jan;5:1-11. doi: 10.1200/CCI.20.00060. PMID: 33411624; PMCID: PMC8140794.

In the Pursuit of Privacy: The Promises and Predicaments of Federated Learning in Healthcare

Published in Frontiers in Artificial Intelligence, 2021

Citation: Topaloglu MY, Morrell EM, Rajendran S, Topaloglu U. In the Pursuit of Privacy: The Promises and Predicaments of Federated Learning in Healthcare. Front Artif Intell. 2021 Oct 6;4:746497. doi: 10.3389/frai.2021.746497. PMID: 34693280; PMCID: PMC8528445.

Predicting criminal recidivism using specialized feature engineering and XGBoost

Published in CrimRxiv, 2021

Citation: Rajendran, S., & Sundararajan, P. (2021). Predicting criminal recidivism using specialized feature engineering and XGBoost. CrimRxiv. https://doi.org/10.21428/cb6ab371.d95f8c48

Distance Traveled to Tertiary Care as Prognostic Indicator in Intracerebral Hemorrhage Outcomes

Published in Society of Critical Care Medicine, 2022

Citation: Rajendran, S. , Ong, T. , Zameza, P. , Wolfe, S. , Topaloglu, U. , Duncan, P. , Anwar, M. , Samuel, R. , Budigi, B. , Lack, C. & Sarwal, A. (2022). 779: DISTANCE TRAVELED TO TERTIARY CARE AS PROGNOSTIC INDICATOR IN INTRACEREBRAL HEMORRHAGE OUTCOMES. Critical Care Medicine, 50 (1), 384-384. doi: 10.1097/01.ccm.0000809440.55714.3d.

Creation of a Proof-of-Concept 3D-Printed Spinal Lateral Access Simulator

Published in Cureus, 2022

Citation: Pullen, M. W., Valero-Moreno, F., Rajendran, S., Shah, V. U., Bruneau, B. R., Martinez, J. L., Ramos-Fresnedo, A., Quinones-Hinojosa, A., & Fox, W. C. (2022). Creation of a Proof-of-Concept 3D-Printed Spinal Lateral Access Simulator. Cureus, 14(5), e25448. https://doi.org/10.7759/cureus.25448

A non-invasive artificial intelligence approach for the prediction of human blastocyst ploidy: A retrospective model development and validation study

Published in The Lancet Digital Health, 2023

Citation: Barnes, J., Brendel, M., Gao, V. R., Rajendran, S., Kim, J., Li, Q., Malmsten, J. E., Sierra, J. T., Zisimopoulos, P., Sigaras, A., Khosravi, P., Meseguer, M., Zhan, Q., Rosenwaks, Z., Elemento, O., Zaninovic, N., & Hajirasouliha, I. (2023). A non-invasive artificial intelligence approach for the prediction of human blastocyst ploidy: a retrospective model development and validation study. The Lancet. Digital health, 5(1), e28–e40. https://doi.org/10.1016/S2589-7500(22)00213-8

Data heterogeneity in federated learning with Electronic Health Records: Case studies of risk prediction for acute kidney injury and sepsis diseases in critical care

Published in PLOS Digital Health, 2023

Citation: Rajendran, S., Xu, Z., Pan, W., Ghosh, A., & Wang, F. (2023). Data heterogeneity in federated learning with Electronic Health Records: Case studies of risk prediction for acute kidney injury and sepsis diseases in critical care. PLOS digital health, 2(3), e0000117. https://doi.org/10.1371/journal.pdig.0000117

Biomedical discovery through the integrative biomedical knowledge hub (iBKH)

Published in Iscience, 2023

Citation: Su, C., Hou, Y., Zhou, M., Rajendran, S., Maasch, J. R. M. A., Abedi, Z., Zhang, H., Bai, Z., Cuturrufo, A., Guo, W., Chaudhry, F. F., Ghahramani, G., Tang, J., Cheng, F., Li, Y., Zhang, R., DeKosky, S. T., Bian, J., & Wang, F. (2023). Biomedical discovery through the integrative biomedical knowledge hub (iBKH). iScience, 26(4), 106460. https://doi.org/10.1016/j.isci.2023.106460

Web-Based Social Networks of Individuals With Adverse Childhood Experiences: Quantitative Study

Published in Journal of Medical Internet Research, 2023

Citation: Cao, Y., Rajendran, S., Sundararajan, P., Law, R., Bacon, S., Sumner, S. A., & Masuda, N. (2023). Web-Based Social Networks of Individuals With Adverse Childhood Experiences: Quantitative Study. Journal of medical Internet research, 25, e45171. https://doi.org/10.2196/45171

Predicting Embryo Ploidy Status Using Time-lapse Images

Published in Human Reproduction, 2023

Citation: S Rajendran and others, O-120 Predicting Embryo Ploidy Status Using Time-lapse Images, Human Reproduction, Volume 38, Issue Supplement_1, June 2023, dead093.147, https://doi.org/10.1093/humrep/dead093.147

An adaptive federated learning framework for clinical risk prediction with electronic health records from multiple hospitals

Published in Cell Patterns, 2024

Citation: Pan, W., Xu, Z., Rajendran, S., & Wang, F. (2023). An adaptive federated learning framework for clinical risk prediction with electronic health records from multiple hospitals. Patterns (New York, N.Y.), 5(1), 100898. https://doi.org/10.1016/j.patter.2023.100898

Learning across diverse biomedical data modalities and cohorts: Challenges and opportunities for innovation

Published in Cell Patterns, 2024

Citation: Rajendran, S., Pan, W., Sabuncu, R. M., Chen, Y., Zhou, J., & Wang, F. (2023). Learning across diverse biomedical data modalities and cohorts: Challenges and opportunities for innovation. Patterns, 100913. https://doi.org/10.1016/j.patter.2023.100913

High-speed optical imaging with sCMOS pixel reassignment

Published in Nature Communications, 2024

Citation: Mandracchia, B., Zheng, C., Rajendran, S. et al. High-speed optical imaging with sCMOS pixel reassignment. Nat Commun 15, 4598 (2024). https://doi.org/10.1038/s41467-024-48987-7

Automatic ploidy prediction and quality assessment of human blastocysts using time-lapse imaging

Published in Nature Communications, 2024

Citation: Rajendran, S., Brendel, M., Barnes, J. et al. Automatic ploidy prediction and quality assessment of human blastocysts using time-lapse imaging. Nat Commun 15, 7756 (2024). https://doi.org/10.1038/s41467-024-51823-7

Effect of Flow Regime on Snowflake Yeast Evolution

Published: April 19, 2019

Here is a link to the poster.

Extracting Smoking Status from Electronic Health Records Using NLP and Deep Learning

Published: May 30, 2020

Predicting criminal recidivism using specialized feature engineering and XGBoost

Published: November 29, 2021

The National Institute of Justice’s (NIJ) “Recidivism Forecasting Challenge” (the Challenge) aims to increase public safety and improve the fair administration of justice across the United States.

Intro to Machine Learning

Published: December 03, 2021

Here is a link to the talk.

Methods and Results for Models Developed to Score Student Responses Using BERT

Published: April 01, 2022

More information here

Federated Learning and Data Heterogeneity

Published: February 05, 2023

Watch the recording here!

Predicting Embryo Ploidy Status Using Time-lapse Images

Published: June 30, 2023

Here is my talk!

FEMI: A Foundation Model for Embryology Trained on Time-lapse Images

Published: July 08, 2023

We presented at ESHRE 2024. Here is my talk!

STEM From Podcast, Where does your journey STEM from?

Published: November 02, 2023

I was on the STEM From podcast with Dr. Carina Minardi. Check it out here.

Teaching experience 1

Undergraduate course, University 1, Department, 2014

This is a description of a teaching experience. You can use markdown like any other post.

Teaching experience 2

Workshop, University 1, Department, 2015

This is a description of a teaching experience. You can use markdown like any other post.