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Published in Clinical Oncology, 2022
Let’s explore a the different machine learning applications for auto-segmentation tools in radiotherapy planning systems
Recommended citation: Harrison K, Pullen H, Welsh C, Oktay O, Alvarez-Valle J, Jena R. Machine Learning for Auto-Segmentation in Radiotherapy Planning. Clin Oncol (R Coll Radiol). 2022 Feb;34(2):74-88. doi: 10.1016/j.clon.2021.12.003. Epub 2022 Jan 5. PMID: 34996682.
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Published in Lancet Digit Health, 2023
Join us in exploring the different ways we can clinically evaluate AI systems for healthcare imaging
Recommended citation: McCague C, MacKay K, Welsh C, Constantinou A, Jena R, Crispin-Ortuzar M; Imaging AI evaluation consensus group. Position statement on clinical evaluation of imaging AI. Lancet Digit Health. 2023 Jul;5(7):e400-e402. doi: 10.1016/S2589-7500(23)00090-0. Erratum in: Lancet Digit Health. 2023 Aug;5(8):e484. doi: 10.1016/S2589-7500(23)00133-4. PMID: 37391263.
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Published in The Turing Way: A handbook for reproducible, ethical, and collaborative research., 2024
Let’s explore a community-developed shared vocabulary of data science risks.
Recommended citation: Data Hazards Chapter, The Turing Way Community. The Turing Way: A handbook for reproducible, ethical, and collaborative research. Zenodo. (2024) https://doi:10.5281/zenodo.3233853
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Published in Open Science Framework - Current Preprint, 2024
Join us in applying the Data Hazards framework to a real research case study and evaluate ethical risks.
Recommended citation: Roman Garcia, S., Welsh, C., Di Cara, N. H., Sterratt, D., Romano, N., & Stefan, M. I. (2024, March 11). Data Hazards as an ethical toolkit for neuroscience. https://doi.org/10.31219/osf.io/yn2j9
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Published in Accepted by the Future Health Journal July, 2024
Join us in exploring community-driven approaches to developing ethical AI for healthcare applications.
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Workshop, University 1, Department, 2015
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