Automated Cellular-Level Dual Global Fusion of Whole-Slide Imaging for Lung Adenocarcinoma Prognosis

• Published in: Cancers Vol. 15; no. 19; p. 4824
• Main Authors: Diao, Songhui, Chen, Pingjun, Showkatian, Eman, Bandyopadhyay, Rukhmini, Rojas, Frank R, Zhu, Bo, Hong, Lingzhi, Aminu, Muhammad, Saad, Maliazurina B, Salehjahromi, Morteza, Muneer, Amgad, Sujit, Sheeba J, Behrens, Carmen, Gibbons, Don L, Heymach, John V, Kalhor, Neda, Wistuba, Ignacio I, Solis Soto, Luisa M, Zhang, Jianjun, Qin, Wenjian, Wu, Jia
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 01.10.2023; MDPI
• Subjects: Adenocarcinoma; Artificial intelligence; Automation; Cancer; cellular architecture; Classification; Datasets; Deep learning; Design and construction; Diagnosis; embedded features; Gene mapping; Genomes; global fusion; Health aspects; lung adenocarcinoma; Lung cancer; Malignancy; Mechanization; Medical diagnosis; Medical prognosis; Methods; Morphology; Oncology, Experimental; Pathology; Patients; Pipelines; Predictions; Prognosis; survival prediction; Tumor microenvironment; whole-slide image; global fusion; cellular architecture; embedded features; survival prediction; whole-slide image; lung adenocarcinoma

Histopathologic whole-slide images (WSI) are generally considered the gold standard for cancer diagnosis and prognosis. Survival prediction based on WSI has recently attracted substantial attention. Nevertheless, it remains a central challenge owing to the inherent difficulties of predicting patient...