Development and Evaluation of Machine Learning in Whole-Body Magnetic Resonance Imaging for Detecting Metastases in Patients With Lung or Colon Cancer: A Diagnostic Test Accuracy Study

OBJECTIVES: Whole-body magnetic resonance imaging (WB-MRI) has been demonstrated to be efficient and cost-effective for cancer staging. The study aim was to develop a machine learning (ML) algorithm to improve radiologists' sensitivity and specificity for metastasis detection and reduce reading...

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Autores principales: Rockall, Andrea G., Li, Xingfeng, Johnson, Nicholas, Lavdas, Ioannis, Santhakumaran, Shalini, Prevost, A. Toby, Punwani, Shonit, Goh, Vicky, Barwick, Tara D., Bharwani, Nishat, Sandhu, Amandeep, Sidhu, Harbir, Plumb, Andrew, Burn, James, Fagan, Aisling, Wengert, Georg J., Koh, Dow-Mu, Reczko, Krystyna, Dou, Qi, Warwick, Jane, Liu, Xinxue, Messiou, Christina, Tunariu, Nina, Boavida, Peter, Soneji, Neil, Johnston, Edward W., Kelly-Morland, Christian, De Paepe, Katja N., Sokhi, Heminder, Wallitt, Kathryn, Lakhani, Amish, Russell, James, Salib, Miriam, Vinnicombe, Sarah, Haq, Adam, Aboagye, Eric O., Taylor, Stuart, Glocker, Ben
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Lippincott Williams & Wilkins 2023
Materias:
Original Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10662596/
https://www.ncbi.nlm.nih.gov/pubmed/37358356
http://dx.doi.org/10.1097/RLI.0000000000000996

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