A micro-XRT image analysis and machine learning methodology for the characterisation of multi- particulate capsule formulations [Video Abstract]
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Doerr, Frederik J.S. and Florence, Alastair J. (2020) A micro-XRT image analysis and machine learning methodology for the characterisation of multi- particulate capsule formulations [Video Abstract]. Elsevier, Amsterdam. (https://doi.org/10.1016/j.ijpx.2020.100041)
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Video.
Filename: Doerr_Florence_IJPX_2020_image_analysis_and_machine_learning_methodology_for_the_characterisation_of_multi_particulate_capsule_video.mp4
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Abstract
Video abstract highlighting aspects of a micro-XRT image analysis and machine learning methodology for the characterisation of multi-particulate capsule formulations (https://doi.org/10.1016/j.ijpx.2020.100041).
ORCID iDs
Doerr, Frederik J.S.
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Item type: Other ID code: 71463 Dates: DateEvent1 December 2020Published15 January 2020Published Online18 November 2019AcceptedSubjects: Medicine > Therapeutics. Pharmacology Department: Faculty of Science > Strathclyde Institute of Pharmacy and Biomedical Sciences
Technology and Innovation Centre > Continuous Manufacturing and Crystallisation (CMAC)
Strategic Research Themes > Advanced Manufacturing and MaterialsDepositing user: Pure Administrator Date deposited: 14 Feb 2020 00:03 Last modified: 11 Nov 2024 16:09 Related URLs: URI: https://strathprints.strath.ac.uk/id/eprint/71463
CORE (COnnecting REpositories)