Deep Learning-Based, Multiclass Approach to Cancer Classification on Liquid Biopsy Data-Reference-Cited by-同舟云学术

Deep Learning-Based, Multiclass Approach to Cancer Classification on Liquid Biopsy Data

Published:2024 Issue: Volume:12 Page:306-313
ISSN:2168-2372
Container-title:IEEE Journal of Translational Engineering in Health and Medicine
language:
Short-container-title:IEEE J. Transl. Eng. Health Med.

Author:

Jopek Maksym A.¹^ORCID,Pastuszak Krzysztof²^ORCID,Cygert Sebastian³^ORCID,Best Myron G.⁴,Wurdinger Thomas⁴,Jassem Jacek⁵,Żaczek Anna J.¹^ORCID,Supernat Anna¹^ORCID

Affiliation:

1. Laboratory of Translational Oncology, Intercollegiate Faculty of Biotechnology, University of Gdańsk, Gdańsk, Poland

2. Centre of Biostatistics and Bioinformatics, Medical University of Gdańsk, Gdańsk, Poland

3. Department of Multimedia Systems, Faculty of Electronics, Telecommunications, Informatics, Gdańsk University of Technology, Gdańsk, Poland

4. Department of Neurosurgery, Amsterdam UMC Locatie AMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands

5. Department of Oncology and Radiotherapy, Medical University of Gdańsk, Gdańsk, Poland

Funder

SONATA Grant of the National Science Centre

Medical University of Gdañsk Statutory Work

National Center for Research and Development through the Lider XI

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/6221039/10325338/10418148.pdf?arnumber=10418148

Reference44 articles.

1. Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries

2. CA125 and Ovarian Cancer: A Comprehensive Review

3. Usefulness of Serum Carcinoembryonic Antigen (CEA) in evaluating response to chemotherapy in patients with advanced non small-cell lung cancer: a prospective cohort study

4. Liquid Biopsy: From Discovery to Clinical Application

5. Contents in tumor-educated platelets as the novel biosource for cancer diagnostics

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