Publications

Published/Accepted

Sagar, D., Dwivedi, T., Gupta, A., Aggarwal, P., Bhatnagar, S., Mohan, A., Kaur, P. & Bhatnagar Sr, S. (2024). Clinical Features Predicting COVID-19 Severity Risk at the Time of Hospitalization. Cureus, 16(3). [ https://pubmed.ncbi.nlm.nih.gov/38690475/ | Impact Factor: 1.2]

Chatterjee R., Sagar D., Pourhomayoun M., Kaur M., & Amini N. (2023, February). Deep Residual Distilled Convolutional Learning For Detection of Large Vessel Occlusion in Ischemic Stroke Patients. In 1st IEEE‬‭ International‬‭ Conference‬‭ on‬‭ Artificial‬‭ Intelligence,‬‭ Medicine,‬‭ Health‬‭ and‬‭ Care‬‭ (AIMHC‬‭ 2024),‬‭ Laguna‬ Hills, California, Feb. 2024. [https://ieeexplore.ieee.org/abstract/document/10504351 | 28.33% Acceptance Rate ]

Sagar, D., Mohammadi F., Pourhomayoun M., Joen J., & Amini N. (2023 October). Deep Learning Based GABA Edited-MRS Signal Reconstruction. In 18th International Symposium on Visual Computing (ISVC 2023), Lake Tahoe, NV, Oct. 2023. [https://link.springer.com/chapter/10.1007/978-3-031-47969-4_2 | 30% Acceptance Rate ]

Sagar, D., Risheh A., Sheikh N. & Forouzesh N. (2023, September). Physics-Guided Deep Generative Model for New Ligand Discovery. In 14th ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics (ACM-BCB 2023), Houston, TX, Sept. 2023. [ ⭐️ Best paper finalist award ⭐️ | https://dl.acm.org/doi/10.1145/3584371.3613067 | 29% Acceptance Rate ]

Sagar, D., Aggarwal, P., Farswan, A., Gupta, R., & Gupta, A. (2022). GCRS: A hybrid graph convolutional network for risk stratification in multiple myeloma cancer patients. Computers in Biology and Medicine, 149, 106048.
[ https://pubmed.ncbi.nlm.nih.gov/36113255/ | Impact Factor: 7.7]

Sagar, D., Garg, J., Kansal, P., Bhalla, S., Shah, R. R., & Yu, Y. (2020, September). PAI-BPR: Personalized outfit recommendation scheme with attribute-wise interpretability. In 2020 IEEE Sixth International Conference on Multimedia Big Data (BigMM 2020) (pp. 221-230). IEEE Virtual Conference. [ https://ieeexplore.ieee.org/abstract/document/9232589 | 19.5% Acceptance Rate]

Theses

Deep Reconstruction Model for Exposing Low Concentration Metabolites in Edited-MRS Brain Scans. [ Ongoing ]

Multiple Myeloma Cancer Cell Instance Segmentation. A tool to detect and segment MM cancer cells from bone marrow aspirate slides using Deep Learning. [ Published as B.Tech Thesis in IIIT Delhi Thesis Archive 2021. | https://arxiv.org/abs/2110.04275 ]