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Literature DB >> 30962976

The promise and challenges of deep learning models for automated histopathologic classification and mutation prediction in lung cancer.

Pradnya D Patil¹, Brian Hobbs², Nathan A Pennell¹.

Abstract

Entities: Disease

Year: 2019 PMID： 30962976 PMCID： PMC6409244 DOI： 10.21037/jtd.2018.12.55

Source DB: PubMed Journal: J Thorac Dis ISSN： 2072-1439 Impact factor: 2.895

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2 in total

1. The 8^th UICC/AJCC TNM edition for non-small cell lung cancer staging: getting off to a flying start?

Authors: Andrea Lancia; Elisa Merizzoli; Andrea Riccardo Filippi
Journal: Ann Transl Med Date: 2019-09

2. Multisite Tumor Sampling Reveals Extensive Heterogeneity of Tumor and Host Immune Response in Ovarian Cancer.

Authors: Sotirios Lakis; Vassiliki Kotoula; Georgia-Angeliki Koliou; Ioannis Efstratiou; Sofia Chrisafi; Alexios Papanikolaou; Pantelis Zebekakis; George Fountzilas
Journal: Cancer Genomics Proteomics Date: 2020 Sep-Oct Impact factor: 4.069

2 in total

The promise and challenges of deep learning models for automated histopathologic classification and mutation prediction in lung cancer.

1. The 8th UICC/AJCC TNM edition for non-small cell lung cancer staging: getting off to a flying start?

2. Multisite Tumor Sampling Reveals Extensive Heterogeneity of Tumor and Host Immune Response in Ovarian Cancer.

1. The 8^th UICC/AJCC TNM edition for non-small cell lung cancer staging: getting off to a flying start?