| Automated detection of diabetic retinopathy using deep learning C Lam, D Yi, M Guo, T Lindsey AMIA summits on translational science proceedings 2018, 147, 2018 | 409 | 2018 |
| Distributed deep learning networks among institutions for medical imaging K Chang, N Balachandar, C Lam, D Yi, J Brown, A Beers, B Rosen, ... Journal of the American Medical Informatics Association 25 (8), 945-954, 2018 | 342 | 2018 |
| Retinal lesion detection with deep learning using image patches C Lam, C Yu, L Huang, D Rubin Investigative ophthalmology & visual science 59 (1), 590-596, 2018 | 214 | 2018 |
| Embolus extravasation is an alternative mechanism for cerebral microvascular recanalization CK Lam, T Yoo, B Hiner, Z Liu, J Grutzendler Nature 465 (7297), 478-482, 2010 | 203 | 2010 |
| Prediction of respiratory decompensation in Covid-19 patients using machine learning: The READY trial H Burdick, C Lam, S Mataraso, A Siefkas, G Braden, RP Dellinger, ... Computers in biology and medicine 124, 103949, 2020 | 165 | 2020 |
| Angiophagy prevents early embolus washout but recanalizes microvessels through embolus extravasation J Grutzendler, S Murikinati, B Hiner, L Ji, CK Lam, T Yoo, S Gupta, ... Science translational medicine 6 (226), 226ra31-226ra31, 2014 | 86 | 2014 |
| Mortality prediction model for the triage of COVID-19, pneumonia, and mechanically ventilated ICU patients: A retrospective study L Ryan, C Lam, S Mataraso, A Allen, A Green-Saxena, E Pellegrini, ... Annals of Medicine and Surgery 59, 207-216, 2020 | 81 | 2020 |
| Visual acuity measured with a smartphone app is more accurate than Snellen testing by emergency department providers AS Pathipati, EH Wood, CK Lam, CS Sáles, DM Moshfeghi Graefe's archive for clinical and experimental ophthalmology 254, 1175-1180, 2016 | 67 | 2016 |
| Optimizing and visualizing deep learning for benign/malignant classification in breast tumors D Yi, RL Sawyer, D Cohn III, J Dunnmon, C Lam, X Xiao, D Rubin arXiv preprint arXiv:1705.06362, 2017 | 59 | 2017 |
| Assessing the effects of data drift on the performance of machine learning models used in clinical sepsis prediction K Rahmani, R Thapa, P Tsou, SC Chetty, G Barnes, C Lam, CF Tso International Journal of Medical Informatics 173, 104930, 2023 | 39 | 2023 |
| Patient perspectives on the efficacy and ergonomics of rechargeable spinal cord stimulators CK Lam, JM Rosenow Neuromodulation: Technology at the Neural Interface 13 (3), 218-223, 2010 | 37 | 2010 |
| Machine learning as a precision-medicine approach to prescribing COVID-19 pharmacotherapy with remdesivir or corticosteroids C Lam, A Siefkas, NS Zelin, G Barnes, RP Dellinger, JL Vincent, G Braden, ... Clinical therapeutics 43 (5), 871-885, 2021 | 27 | 2021 |
| Phototherapeutic keratectomy for epithelial basement membrane dystrophy WS Lee, CK Lam, EE Manche Clinical ophthalmology, 15-22, 2016 | 24 | 2016 |
| Segmentation-assisted fully convolutional neural network enhances deep learning performance to identify proliferative diabetic retinopathy M Alam, EJ Zhao, CK Lam, DL Rubin Journal of Clinical Medicine 12 (1), 385, 2023 | 14 | 2023 |
| Multitask learning with recurrent neural networks for acute respiratory distress syndrome prediction using only electronic health record data: model development and validation … C Lam, R Thapa, J Maharjan, K Rahmani, CF Tso, NP Singh, ... JMIR Medical Informatics 10 (6), e36202, 2022 | 14 | 2022 |
| Personalized stratification of hospitalization risk amidst COVID-19: A machine learning approach C Lam, J Calvert, A Siefkas, G Barnes, E Pellegrini, A Green-Saxena, ... Health policy and technology 10 (3), 100554, 2021 | 12 | 2021 |
| Is machine learning a better way to identify COVID-19 patients who might benefit from hydroxychloroquine treatment?—the IDENTIFY trial H Burdick, C Lam, S Mataraso, A Siefkas, G Braden, RP Dellinger, ... Journal of clinical medicine 9 (12), 3834, 2020 | 12 | 2020 |
| Retrospective validation of a machine learning clinical decision support tool for myocardial infarction risk stratification S Panchavati, C Lam, NS Zelin, E Pellegrini, G Barnes, J Hoffman, ... Healthcare technology letters 8 (6), 139-147, 2021 | 11 | 2021 |
| Semi-supervised deep learning from time series clinical data for acute respiratory distress syndrome prediction: model development and validation study DR Lam C, Tso CF, Green-Saxena A, Pellegrini E, Iqbal Z, Evans D, Hoffman J ... JMIR Form Res, 2021 | 10* | 2021 |
| Machine learning early prediction of respiratory syncytial virus in pediatric hospitalized patients CF Tso, C Lam, J Calvert, Q Mao Frontiers in Pediatrics 10, 886212, 2022 | 9 | 2022 |
Jacob CalvertPostdoctoral Fellow, Georgia Institute of Technology在 gatech.edu 的电子邮件经过验证
