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Harriet L. Lancaster

affiliation not provided to SSRN

  • affiliation not provided to SSRN

SCHOLARLY PAPERS

2

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Scholarly Papers (2)

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1.

AI Performance for Nodule Volume Doubling Time in the follow-up of the UKLS Lung Cancer Screening Study Compared to Expert Consensus and Histological Validation

Number of pages: 25 Posted: 13 Oct 2025
Beibei Jiang, Harriet L. Lancaster, Michael P.A. Davies, Jan-Willem C. Gratama, Mario Silva, Daiwei Han, Jaeyoun Yi, Carlijn M. van der Aalst, Anand Devaraj, Marjolein A. Heuvelmans, John K. Field and Matthijs Oudkerk
affiliation not provided to SSRN, affiliation not provided to SSRN, University of Liverpool, Gelre Ziekenhuizen, University of Parma, affiliation not provided to SSRN, affiliation not provided to SSRN, Erasmus University Rotterdam (EUR) - Erasmus Medical Center (MC), Imperial College London - National Heart and Lung Institute, affiliation not provided to SSRN, University of Liverpool and University of Groningen - University Medical Center Groningen
Downloads 40 (1,196,171)

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Artificial Intelligence, Lung Cancer Screening, pulmonary nodule, VDT, growth-rate, screening follow-up, Low-Dose CT, Computed Tomography, Comparative Study

2.

Volume and location of lung cancer from screen-detected nodules to two-years follow-up: Post hoc analysis from the UK Lung Cancer Screening (UKLS) Trial

Number of pages: 32 Posted: 16 Dec 2025
Oke Dimas Asmara, Harriet L. Lancaster, John K. Field, Michael P.A. Davies, Stephen W. Duffy, Christiaan Boerma, Edith Visser, Kim de Jong, Anand Devaraj, Marjolein A. Heuvelmans, Wouter H. van Geffen and M. OUDKERK
University of Groningen, affiliation not provided to SSRN, University of Liverpool, University of Liverpool, Queen Mary University of London, University of Groningen, affiliation not provided to SSRN, affiliation not provided to SSRN, Imperial College London - National Heart and Lung Institute, affiliation not provided to SSRN, affiliation not provided to SSRN and affiliation not provided to SSRN
Downloads 39 (1,196,171)

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Lung cancer, screening, location, volume, UKLS