Cross-attention enables deep learning on limited omics-imaging-clinical data of 130 lung cancer patients-Reference-Cited by-同舟云学术

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Cross-attention enables deep learning on limited omics-imaging-clinical data of 130 lung cancer patients

Published:2024-07 Issue:7 Volume:4 Page:100817
ISSN:2667-2375
Container-title:Cell Reports Methods
language:en
Short-container-title:Cell Reports Methods

Author:

Verma Suraj,Magazzù Giuseppe,Eftekhari Noushin,Lou Thai,Gilhespy Alex,Occhipinti Annalisa,Angione Claudio^ORCID

Funder

EPSRC

Friends for an Earlier Breast Cancer Test

National Biofilms Innovation Centre

The Alan Turing Institute

Publisher

Elsevier BV

Reference124 articles.

1. Epidemiology of lung cancer;Thandra;Contemp. Oncol.,2021

2. Trends in survival rates of non–small cell lung cancer with use of molecular testing and targeted therapy in korea, 2010-2020;Chi;JAMA Netw. Open,2023

3. Mechanisms of resistance to chemotherapy in non-small cell lung cancer;Min;Arch Pharm. Res. (Seoul),2021

4. Lung cancer survival only increases by a small amount despite recent treatment advances;Bagcchi;Lancet Respir. Med.,2017

5. A highly predictive autoantibody-based biomarker panel for prognosis in early-stage nsclc with potential therapeutic implications;Patel;Br. J. Cancer,2022

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1. Radiogenomics: bridging the gap between imaging and genomics for precision oncology;MedComm;2024-09

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