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Call for Special Issue Papers: Enhancing In Vitro Toxicology Through Machine Learning

Call for Special Issue Papers: Enhancing In Vitro Toxicology Through Machine Learning APPLIED IN VITRO TOXICOLOGY CALL FOR PAPERS Volume 8, Number 1, 2022 ª Mary Ann Liebert, Inc. DOI: 10.1089/aivt.2022.29027.cfp Open camera or QR reader and scan code to access this article and other resources online. Call for Special Issue Papers: Enhancing In Vitro Toxicology Through Machine Learning Deadline for Manuscript Submission: August 15, 2022 Guest Editor: Brett A. Lidbury, PhD, FFSc (RCPA), The Australian National University, Canberra, Australia Applied In Vitro Toxicology is calling for original research, commentary and review manuscripts that address the application of machine learning ( ML) to in vitro toxicology. The particular emphasis is innovation that results in the replacement of animals in toxicology assessment and experiments. A previous AIVT special issue centered on the integration of multiple sources of in- formation; for this issue we are interested specifically in the melding of hu- man data analytics with human cell and tissue systems that advance in vitro toxicology. Fundamental research in this field is blossoming, with a recent search on PubMed revealing a 5-fold increase in ML AND toxicology publications (28/ 144) between 2016 to 2021. With this level of interest, now is the time to synthesise and translate fundamental research into day-to-day technologies and http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Applied In Vitro Toxicology Mary Ann Liebert

Call for Special Issue Papers: Enhancing In Vitro Toxicology Through Machine Learning

Applied In Vitro Toxicology , Volume 8 (1): 1 – Mar 1, 2022

Call for Special Issue Papers: Enhancing In Vitro Toxicology Through Machine Learning

Applied In Vitro Toxicology , Volume 8 (1): 1 – Mar 1, 2022

Abstract

APPLIED IN VITRO TOXICOLOGY CALL FOR PAPERS Volume 8, Number 1, 2022 ª Mary Ann Liebert, Inc. DOI: 10.1089/aivt.2022.29027.cfp Open camera or QR reader and scan code to access this article and other resources online. Call for Special Issue Papers: Enhancing In Vitro Toxicology Through Machine Learning Deadline for Manuscript Submission: August 15, 2022 Guest Editor: Brett A. Lidbury, PhD, FFSc (RCPA), The Australian National University, Canberra, Australia Applied In Vitro Toxicology is calling for original research, commentary and review manuscripts that address the application of machine learning ( ML) to in vitro toxicology. The particular emphasis is innovation that results in the replacement of animals in toxicology assessment and experiments. A previous AIVT special issue centered on the integration of multiple sources of in- formation; for this issue we are interested specifically in the melding of hu- man data analytics with human cell and tissue systems that advance in vitro toxicology. Fundamental research in this field is blossoming, with a recent search on PubMed revealing a 5-fold increase in ML AND toxicology publications (28/ 144) between 2016 to 2021. With this level of interest, now is the time to synthesise and translate fundamental research into day-to-day technologies and

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Publisher
Mary Ann Liebert
Copyright
Copyright 2022, Mary Ann Liebert, Inc., publishers
ISSN
2332-1512
eISSN
2332-1539
DOI
10.1089/aivt.2022.29027.cfp
Publisher site
See Article on Publisher Site

Abstract

APPLIED IN VITRO TOXICOLOGY CALL FOR PAPERS Volume 8, Number 1, 2022 ª Mary Ann Liebert, Inc. DOI: 10.1089/aivt.2022.29027.cfp Open camera or QR reader and scan code to access this article and other resources online. Call for Special Issue Papers: Enhancing In Vitro Toxicology Through Machine Learning Deadline for Manuscript Submission: August 15, 2022 Guest Editor: Brett A. Lidbury, PhD, FFSc (RCPA), The Australian National University, Canberra, Australia Applied In Vitro Toxicology is calling for original research, commentary and review manuscripts that address the application of machine learning ( ML) to in vitro toxicology. The particular emphasis is innovation that results in the replacement of animals in toxicology assessment and experiments. A previous AIVT special issue centered on the integration of multiple sources of in- formation; for this issue we are interested specifically in the melding of hu- man data analytics with human cell and tissue systems that advance in vitro toxicology. Fundamental research in this field is blossoming, with a recent search on PubMed revealing a 5-fold increase in ML AND toxicology publications (28/ 144) between 2016 to 2021. With this level of interest, now is the time to synthesise and translate fundamental research into day-to-day technologies and

Journal

Applied In Vitro ToxicologyMary Ann Liebert

Published: Mar 1, 2022

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