| Assemblies-of-putative-SARS-CoV2-spike-encoding-mRNA-sequences-for-vaccines-BNT-162b2-and-mRNA-1273 DE Jeong, M McCoy, K Artiles, O Ilbay, A Fire, K Nadeau, H Park, B Betts, ... GitHub, no. i, 0-3, 2021 | 29 | 2021 |
| Computing the hazard ratios associated with explanatory variables using machine learning models of survival data S Sundrani, J Lu JCO Clinical Cancer Informatics 5, 364-378, 2021 | 18 | 2021 |
| Predicting patient decompensation from continuous physiologic monitoring in the emergency department S Sundrani, J Chen, BT Jin, ZSH Abad, P Rajpurkar, D Kim NPJ Digital Medicine 6 (1), 60, 2023 | 8 | 2023 |
| Bioinspired Functional Gradients for Toughness Augmentation in Synthetic Polymer Systems K Chorazewicz, S Sundrani, BK Ahn Macromolecular Chemistry and Physics 219 (15), 1800134, 2018 | 3 | 2018 |
| DNA polymerase diversity reveals multiple incursions of Polintons during nematode evolution DE Jeong, S Sundrani, RN Hall, M Krupovic, EV Koonin, AZ Fire Molecular Biology and Evolution 40 (12), msad274, 2023 | 2 | 2023 |
| Characterization of exposure–response relationships of ipatasertib in patients with metastatic castration-resistant prostate cancer in the IPATential150 study N Kotani, JJ Wilkins, JR Wade, S Dang, DS Sutaria, K Yoshida, ... Cancer Chemotherapy and Pharmacology 90 (6), 511-521, 2022 | 2 | 2022 |
| A Supervised Learning Approach to Predicting Regional Maternal Mortality Risk in Nigeria S Sundrani, A Zhang, C Wendlandt Nigeria, 2020 | 2 | 2020 |
| The STEMentors Program: Promoting the Academic Readiness and Community Building of Students within General Chemistry D DeWeese, JE Nardo, I Applebaum, S Sundrani, A Zur, RM Waymouth, ... Journal of Chemical Education 101 (1), 88-96, 2023 | | 2023 |
| Meta-Learning for Better Learning: Using Meta-Learning Methods to Automatically Label Exam Questions with Detailed Learning Objectives A Zur, I Applebaum, J Nardo, D DeWeese, S Sundrani, S Salehi Proceedings of the 16th International Conference on Educational Data Mining …, 2023 | | 2023 |
| A Deep Learning Approach to Population Based COVID-19 Case Prediction in the US S Sundrani, A Zhang | | |
