FIGURE 1 from Use of Deep Learning to Evaluate Tumor Microenvironmental Features for Prediction of Colon Cancer Recurrence

Frank A. Sinicrope; Garth D. Nelson; Bahar Saberzadeh-Ardestani; Diana I. Segovia; Rondell P. Graham; Christina Wu; Catherine E. Hagen; Sameer Shivji; Paul Savage; Daniel D. Buchanan; Mark A. Jenkins; Amanda I. Phipps; Carol J. Swallow; Loı̈c Le Marchand; Steven Gallinger; Robert C. Grant; Reetesh K. Pai; Stephen N. Sinicrope; Dongyao Yan; Kandavel Shanmugam; James Conner; David P. Cyr; Richard Kirsch; Imon Banerjee; Steve R. Alberts; Qian Shi; Rish K. Pai

doi:10.1158/2767-9764.25888384.v1

Abstract

QuantCRC detects tumor morphologic features in four layers. TB/PDC, tumor budding/poorly differentiated cluster; TIL, tumor-infiltrating lymphocytes. https://cloud.aiforia.com/Public/MayoUpmcAiforia_Pai/0z9TK9WQComQSW5MOEo_1KieA8U9KX9oCFbc2SQ-ioM0. To see the QuantCRC analysis click on the image, then click on “analyze,” and then click on the thumbnail of the image.

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Sinicrope et al. (2024) studied this question.

synapsesocial.com/papers/68e68bffb6db6435876140e3 https://doi.org/10.1158/2767-9764.25888384.v1

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FIGURE 1 from Use of Deep Learning to Evaluate Tumor Microenvironmental Features for Prediction of Colon Cancer Recurrence

Abstract

Discussion

Cite This Study

FIGURE 1 from Use of Deep Learning to Evaluate Tumor Microenvironmental Features for Prediction of Colon Cancer Recurrence

Abstract

Discussion

Cite This Study

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