 Connection
Harrison Bai to Prospective Studies
This is a "connection" page, showing publications Harrison Bai has written about Prospective Studies.
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Connection Strength |
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0.240 |
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Zhao L, Imami MR, Wang Y, Mao Y, Hsu WC, Chen R, Mena E, Li Y, Tang J, Wu J, Voter AF, Amindarolzarbi A, Kargilis D, Afyouni S, Gafita A, Chen J, Chin BB, Leal JP, Du Y, Lin G, Jiao Z, Choyke PL, Rowe SP, Pomper MG, Liao W, Bai HX. Artificial intelligence-based lesion characterization and outcome prediction of prostate cancer on [18F]DCFPyL PSMA imaging. Radiother Oncol. 2026 01; 214:111265.
Score: 0.095
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Peng J, Kim DD, Patel JB, Zeng X, Huang J, Chang K, Xun X, Zhang C, Sollee J, Wu J, Dalal DJ, Feng X, Zhou H, Zhu C, Zou B, Jin K, Wen PY, Boxerman JL, Warren KE, Poussaint TY, States LJ, Kalpathy-Cramer J, Yang L, Huang RY, Bai HX. Deep learning-based automatic tumor burden assessment of pediatric high-grade gliomas, medulloblastomas, and other leptomeningeal seeding tumors. Neuro Oncol. 2022 02 01; 24(2):289-299.
Score: 0.073
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Li Y, Zhuo Z, Weng J, Haller S, Bai HX, Li B, Liu X, Zhu M, Wang Z, Li J, Qiu X, Liu Y. A deep learning model for differentiating paediatric intracranial germ cell tumour subtypes and predicting survival with MRI: a multicentre prospective study. BMC Med. 2024 09 11; 22(1):375.
Score: 0.022
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Yi T, Pan I, Collins S, Chen F, Cueto R, Hsieh B, Hsieh C, Smith JL, Yang L, Liao WH, Merck LH, Bai H, Merck D. DICOM Image ANalysis and Archive (DIANA): an Open-Source System for Clinical AI Applications. J Digit Imaging. 2021 12; 34(6):1405-1413.
Score: 0.018
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Fang S, Bai HX, Fan X, Li S, Zhang Z, Jiang T, Wang Y. A Novel Sequence: ZOOMit-Blood Oxygen Level-Dependent for Motor-Cortex Localization. Neurosurgery. 2020 02 01; 86(2):E124-E132.
Score: 0.016
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Wu J, Bai HX, Chan L, Su C, Zhang PJ, Yang L, Zhang Z. Sublobar resection compared with stereotactic body radiation therapy and ablation for early stage non-small cell lung cancer: A National Cancer Database study. J Thorac Cardiovasc Surg. 2020 Nov; 160(5):1350-1357.e11.
Score: 0.016
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Connection Strength
The connection strength for concepts is the sum of the scores for each matching publication.
Publication scores are based on many factors, including how long ago they were written and whether the person is a first or senior author.
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