Author Response to Peer Reviews of “A Machine Learning Explanation of the Pathogen-Immune Relationship of SARS-CoV-2 (COVID-19), and a Model to Predict Immunity and Therapeutic Opportunity: A Comparative Effectiveness Research Study”

Detalles Bibliográficos
Autor principal: Luellen, Eric
Formato: Online Artículo Texto
Lenguaje:English
Publicado: JMIR Publications 2020
Materias:
Authors’ Response to Peer Reviews
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10414356/
http://dx.doi.org/10.2196/24739
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author Luellen, Eric
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spelling pubmed-104143562023-09-12 Author Response to Peer Reviews of “A Machine Learning Explanation of the Pathogen-Immune Relationship of SARS-CoV-2 (COVID-19), and a Model to Predict Immunity and Therapeutic Opportunity: A Comparative Effectiveness Research Study” Luellen, Eric JMIRx Med Authors’ Response to Peer Reviews JMIR Publications 2020-10-19 /pmc/articles/PMC10414356/ http://dx.doi.org/10.2196/24739 Text en ©Eric Luellen. Originally published in JMIRx Med (https://med.jmirx.org), 19.10.2020. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the JMIRx Med, is properly cited. The complete bibliographic information, a link to the original publication on https://med.jmirx.org/, as well as this copyright and license information must be included.
spellingShingle Authors’ Response to Peer Reviews
Luellen, Eric
Author Response to Peer Reviews of “A Machine Learning Explanation of the Pathogen-Immune Relationship of SARS-CoV-2 (COVID-19), and a Model to Predict Immunity and Therapeutic Opportunity: A Comparative Effectiveness Research Study”
title Author Response to Peer Reviews of “A Machine Learning Explanation of the Pathogen-Immune Relationship of SARS-CoV-2 (COVID-19), and a Model to Predict Immunity and Therapeutic Opportunity: A Comparative Effectiveness Research Study”
title_full Author Response to Peer Reviews of “A Machine Learning Explanation of the Pathogen-Immune Relationship of SARS-CoV-2 (COVID-19), and a Model to Predict Immunity and Therapeutic Opportunity: A Comparative Effectiveness Research Study”
title_fullStr Author Response to Peer Reviews of “A Machine Learning Explanation of the Pathogen-Immune Relationship of SARS-CoV-2 (COVID-19), and a Model to Predict Immunity and Therapeutic Opportunity: A Comparative Effectiveness Research Study”
title_full_unstemmed Author Response to Peer Reviews of “A Machine Learning Explanation of the Pathogen-Immune Relationship of SARS-CoV-2 (COVID-19), and a Model to Predict Immunity and Therapeutic Opportunity: A Comparative Effectiveness Research Study”
title_short Author Response to Peer Reviews of “A Machine Learning Explanation of the Pathogen-Immune Relationship of SARS-CoV-2 (COVID-19), and a Model to Predict Immunity and Therapeutic Opportunity: A Comparative Effectiveness Research Study”
title_sort author response to peer reviews of “a machine learning explanation of the pathogen-immune relationship of sars-cov-2 (covid-19), and a model to predict immunity and therapeutic opportunity: a comparative effectiveness research study”
topic Authors’ Response to Peer Reviews
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10414356/
http://dx.doi.org/10.2196/24739
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