TABLE 3 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:10.1158/2767-9764.25888360

Abstract

Multivariable models for the prediction of TTR by morphologic features and clinicopathological variables in the validation cohort [p-MMR (n = 1,094) or d-MMR (n = 176) stage III colon cancers]

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Sinicrope et al. (2024) studied this question.

synapsesocial.com/papers/68e68bffb6db6435876140d7 https://doi.org/10.1158/2767-9764.25888360

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Abstract

Multivariable models for the prediction of TTR by morphologic features and clinicopathological variables in the validation cohort [p-MMR (n = 1,094) or d-MMR (n = 176) stage III colon cancers]

TABLE 3 from Use of Deep Learning to Evaluate Tumor Microenvironmental Features for Prediction of Colon Cancer Recurrence

Abstract

Discussion

Cite This Study

TABLE 3 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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