| Pytorch: An imperative style, high-performance deep learning library A Paszke, S Gross, F Massa, A Lerer, J Bradbury, G Chanan, T Killeen, ... Advances in neural information processing systems 32, 2019 | 44316 | 2019 |
| Deep learning algorithms for detection of critical findings in head CT scans: a retrospective study S Chilamkurthy, R Ghosh, S Tanamala, M Biviji, NG Campeau, ... The Lancet 392 (10162), 2388-2396, 2018 | 814 | 2018 |
| Pytorch: An imperative style, high-performance deep learning library, 2019 A Paszke, S Gross, F Massa, A Lerer, J Bradbury, G Chanan, T Killeen, ... arXiv preprint arXiv:1912.01703 10, 1912 | 185 | 1912 |
| 2D-3D fully convolutional neural networks for cardiac MR segmentation J Patravali, S Jain, S Chilamkurthy Statistical Atlases and Computational Models of the Heart. ACDC and MMWHS …, 2018 | 140 | 2018 |
| Development and validation of deep learning algorithms for detection of critical findings in head CT scans S Chilamkurthy, R Ghosh, S Tanamala, M Biviji, NG Campeau, ... arXiv preprint arXiv:1803.05854, 2018 | 119 | 2018 |
| Advances in Neural Information Processing Systems 32 ed H A Paszke, S Gross, F Massa, A Lerer, J Bradbury, G Chanan, T Killeen, ... Wallach et al 8024, 2019 | 52 | 2019 |
| A 2017 guide to semantic segmentation with deep learning S Chilamkurthy Available at blog. qure. ai/notes/semantic-segmentation-deep-learning-review …, 2017 | 35 | 2017 |
| SkullBreak/SkullFix–Dataset for automatic cranial implant design and a benchmark for volumetric shape learning tasks O Kodym, J Li, A Pepe, C Gsaxner, S Chilamkurthy, J Egger, M Španěl Data in Brief 35, 106902, 2021 | 25 | 2021 |
| PyTorch: An imperative style, high-performance deep learning library.(NeurIPS)(2019) A Paszke, S Gross, F Massa, A Lerer, J Bradbury, G Chanan, T Killeen, ... | 14 | 1912 |
| PyTorch: An imperative style, high-performance deep learning library. arXiv [cs. LG] A Paszke, S Gross, F Massa, A Lerer, J Bradbury, G Chanan, T Killeen, ... arXiv preprint arXiv:1912.01703, 2019 | 13 | 2019 |
| Parameter estimation of linear and quadratic chirps by employing the fractional Fourier transform and a generalized time frequency transform SB Sahay, T Meghasyam, RK Roy, G Pooniwala, S Chilamkurthy, ... Sadhana 40, 1049-1075, 2015 | 11 | 2015 |
| & Chintala, S.(2019) A Paszke, S Gross, F Massa, A Lerer, J Bradbury, G Chanan, T Killeen, ... Pytorch: An imperative style, high-performance deep learning library …, 0 | 10 | |
| Keras tutorial–traffic sign recognition S Chilamkurthy | 9 | 2017 |
| Deep-aspects: A segmentation-assisted model for stroke severity measurement U Upadhyay, M Ranjan, S Golla, S Tanamala, P Sreenivas, ... European Conference on Computer Vision, 330-339, 2022 | 6 | 2022 |
| Automated lateral ventricular and cranial vault volume measurements in 13,851 patients using deep learning algorithms GA Maragkos, AS Filippidis, S Chilamkurthy, MM Salem, S Tanamala, ... World Neurosurgery 148, e363-e373, 2021 | 6* | 2021 |
| Morphology of the brain: changes in ventricular and cranial vault volumes in 15000 subjects with aging and hydrocephalus S Chilamkurthy, P Rao, G Maragkos, A Thomas Qure. ai, Beth Israel Deaconess Medical Center March 11, 2019 | 2 | 2019 |
| Mind the Clot: Automated LVO Detection on CTA Using Deep Learning S Kumar, A Agarwal, S Golla, S Tanamala, U Upadhyay, S Chattoraj, ... Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2023 | 1 | 2023 |
| Monitoring brain CT scan image U Upadhyay, SK Golla, S Tanamala, S Chilamkurthy, P Putha US Patent 11,501,437, 2022 | 1 | 2022 |
| Ai improves stroke diagnosis and care at a low resource hospital in india U Upadhyay, J Webster, S Tanamala, S Chilamkurthy, S Golla, ... Journal of the Neurological Sciences 429, 2021 | 1 | 2021 |
| Deep learning and medical diagnosis–Authors' reply S Chilamkurthy, S Tanamala The Lancet 394 (10210), 1711, 2019 | 1 | 2019 |
