| Comparing scientific abstracts generated by ChatGPT to real abstracts with detectors and blinded human reviewers CA Gao, FM Howard, NS Markov, EC Dyer, S Ramesh, Y Luo, ... NPJ Digital Medicine 6 (1), 75, 2023 | 876* | 2023 |
| Uncertainty-informed deep learning models enable high-confidence predictions for digital histopathology JM Dolezal, A Srisuwananukorn, D Karpeyev, S Ramesh, S Kochanny, ... Nature communications 13 (1), 6572, 2022 | 95 | 2022 |
| Self-supervised attention-based deep learning for pan-cancer mutation prediction from histopathology OL Saldanha, CML Loeffler, JM Niehues, M van Treeck, TP Seraphin, ... NPJ Precision Oncology 7 (1), 35, 2023 | 62 | 2023 |
| Deep learning generates synthetic cancer histology for explainability and education JM Dolezal, R Wolk, HM Hieromnimon, FM Howard, A Srisuwananukorn, ... npj Precision Oncology 7 (49), 2023 | 42 | 2023 |
| Slideflow: deep learning for digital histopathology with real-time whole-slide visualization JM Dolezal, S Kochanny, E Dyer, S Ramesh, A Srisuwananukorn, ... BMC bioinformatics 25 (1), 134, 2024 | 36* | 2024 |
| Applications of artificial intelligence in pediatric oncology: a systematic review S Ramesh, S Chokkara, T Shen, A Major, SL Volchenboum, ... JCO Clinical Cancer Informatics 5, 1208-1219, 2021 | 26 | 2021 |
| Predicting response to chemotherapy in patients with newly diagnosed high-risk neuroblastoma: a report from the International Neuroblastoma Risk Group A Mayampurath, S Ramesh, D Michael, L Liu, N Feinberg, M Granger, ... JCO Clinical Cancer Informatics 5, 1181-1188, 2021 | 11 | 2021 |
| Examining the inclusivity of US trials of COVID-19 treatment S Chokkara, A Volerman, S Ramesh, N Laiteerapong Journal of General Internal Medicine 36, 1443-1445, 2021 | 9 | 2021 |
| Quantum computing for oncology S Ramesh, T Tomesh, SJ Riesenfeld, FT Chong, AT Pearson Nature Cancer, 1-6, 2024 | 4 | 2024 |
| Applications of deep learning in endocrine neoplasms S Ramesh, JM Dolezal, AT Pearson Surgical Pathology Clinics 16 (1), 167-176, 2023 | 3 | 2023 |
| Artificial intelligence-based cancer progression prediction of oral premalignant lesions via self-supervised deep learning on histopathology. S Ramesh, JM Dolezal, S Kochanny, E Lanzel, YL Chang, CT Wu, CI Jan, ... JCO Global Oncology 9 (Supplement_1), 90-90, 2023 | 2 | 2023 |
| Generative adversarial networks accurately reconstruct pan-cancer histology from pathologic, genomic, and radiographic latent features FM Howard, HM Hieromnimon, S Ramesh, J Dolezal, S Kochanny, ... Science Advances 10 (46), eadq0856, 2024 | 1 | 2024 |
| Developing a low-cost, open-source, locally manufactured workstation and computational pipeline for automated histopathology evaluation using deep learning D Choudhury, JM Dolezal, E Dyer, S Kochanny, S Ramesh, FM Howard, ... EBioMedicine 107, 2024 | 1 | 2024 |
| Interpretable artificial intelligence-based analysis for morphologic classification of neuroblastic tumors. S Ramesh, M Pomaville, K Doytcheva, JM Dolezal, S Kochanny, ... Journal of Clinical Oncology 42 (16_suppl), 10023-10023, 2024 | 1 | 2024 |
| Predicting response to chemotherapy in neuroblastoma using deep learning: A report from the International Neuroblastoma Risk Group. S Ramesh, D Michael, L Liu, N Feinberg, M Granger, A Naranjo, SL Cohn, ... Journal of Clinical Oncology 39 (15_suppl), 10039-10039, 2021 | 1 | 2021 |
| Artificial intelligence-based morphologic classification and molecular characterization of neuroblastic tumors from digital histopathology S Ramesh, E Dyer, M Pomaville, K Doytcheva, J Dolezal, S Kochanny, ... npj Precision Oncology 8 (1), 255, 2024 | | 2024 |
| Methods for Improving Classical SIR Disease Projection Models through Bayesian Parameter Estimation S Chokkara, A Panda, S Ramesh, J Rojas Society of General Internal Medicine, 2020 | | 2020 |
| Environmental Infection Risks for Outdoor Athletes S Ramesh, SP Jariwala, DA Hewitt Journal of Environmental Health 83 (3), 22-27, 2020 | | 2020 |
| Early Surgical Treatment of Intact Juvenile Osteochondritis Dissecans Lesions: A Cost Effectiveness Analysis with Implications For Future Prospective Study Design S Ramesh, C Ramos, JTR Lawrence Pediatrics 144 (2_MeetingAbstract), 766-766, 2019 | | 2019 |
| RISK FACTORS PREVENTING RETURN TO BASELINE ACTIVITY LEVEL AFTER BANKART REPAIR JT Aoyama, S Simmons, T Young-Hamilton, M Horn, S Ramesh, L Wells Orthopaedic Journal of Sports Medicine 7 (3_suppl), 2325967119S00054, 2019 | | 2019 |
Alexander T PearsonUniversity of ChicagoAdresse e-mail validée de medicine.bsd.uchicago.edu