Research Data Leeds Repository
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Items where Author is "McLaughlan, James R."
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Dataset
McLaughlan, James R. and Howell, Lewis and Ingram, Nicola (2024) Lung ultrasound COVID phantom dataset used for training machine learning model. University of Leeds. [Dataset] https://doi.org/10.5518/1485
Ye, Sunjie and Connell, Simon D. and McLaughlan, James R. and Roach, Lucien and Aslam, Zabeada and Chankhunthod, Navadecho and Brown, Andrew and Brydson, Rik and Bushby, Richard J. and Critchley, Kevin and Coletta, P. Louise and Markham, Alexander F. and Evans, Stephen D. (2020) Data associated with 'One-step Preparation of Biocompatible Gold Nanoplates with Controlled Thickness and Adjustable Optical Properties for Plasmon-based Applications'. University of Leeds. [Dataset] https://doi.org/10.5518/790
Batchelor, Damien V. B. and Abou-Saleh, Radwa H. and Coletta, P. Louise and Peyman, Sally A. and McLaughlan, James R. and Evans, Stephen D. (2020) Dataset associated with "Nested-Nanobubbles for Ultrasound Triggered Drug Release". University of Leeds. [Dataset] https://doi.org/10.5518/789
Bourn, Matthew D. and Batchelor, Damien V. B. and Ingram, Nicola and McLaughlan, James R. and Coletta, P. Louise and Evans, Stephen D. and Peyman, Sally A. (2020) High-throughput Microfluidics for Evaluating Microbubble Enhanced Delivery of Cancer Therapeutics in Spheroid Cultures - Dataset. University of Leeds. [Dataset] https://doi.org/10.5518/777
Abou-Saleh, Radwa H. and McLaughlan, James R. and Bushby, Richard J. and Johnson, Benjamin and Freear, Steven and Evans, Stephen D. and Thomson, Neil H. (2019) Impact on microbubble physical and mechanical properties – dataset. University of Leeds. [Dataset] https://doi.org/10.5518/538
Ye, Sunjie and Wheeler, May C. and McLaughlan, James R. and Tamang, Abiral and Diggle, Christine P. and Cespedes, Oscar and Markham, Alexander F. and Coletta, P. Louise and Evans, Stephen D. (2018) Dataset associated with 'Developing Hollow-channel Gold Nanoflowers as Trimodal Intracellular Nanoprobes'. University of Leeds. [Dataset] https://doi.org/10.5518/408