This page is current as of 15.04 2023 06:00 CEST (the rolling issue is planned to be open until 06/2023)

Call for Papers – AI for Life

[1.] Please read the pre-editorial to see what kind of papers we are soliciting for this rolling *) special issue:

https://doi.org/10.1016/j.nbt.2023.02.001

*) A “rolling” issue means that authors can submit papers anytime until the final deadline, and these will be reviewed and published as soon as possible (“rolling”). This benefits both the authors, who don’t have to wait until the deadline to submit, and the reviewers, who won’t be overloaded with a bunch of papers all at once.

Special Issue on Artificial Intelligence for the Life Sciences. In: Elsevier New Biotechnology, IF (2021) 6.490, Q1 9/79 in Biochemical Research Methods, Q1 24/158 in Biotechnology

https://www.journals.elsevier.com/new-biotechnology/forthcoming-special-issues/artificial-intelligence-for-life-sciences

[2.] Submit your paper via the Editorial Manager here:

https://www.editorialmanager.com/nbiot

Artificial Intelligence for Life

Artificial Intelligence (AI) is currently on everyone’s lips as a result of popular successes of statistical machine learning (e.g., deep learning transformer architectures such as chat-GPT *), and btw this shows how important trust is). AI is now pervasive in the life sciences, too. When AI advances are combined with biotechnology advances it is obvious that unprecedented new potential solutions become available. This can help with many global one health issues while also contributing to important Sustainable Development Goals.

Manuscripts on theory and methods for solving problems with AI in the life sciences environment are sought for this special issue. Machine learning and Big Data analytics, knowledge discovery and data mining, biomedical ontologies and knowledge reasoning, knowledge-based reasoning, natural language processing, decision support and reasoning under uncertainty, temporal and spatial representation and inference, explainable AI (XAI), trustworthy AI and other topics are covered.

*) Chat-GPT shows the importance of re-traceability, interpretability and explainability in an impressive way and demonstrates how important the question of “Can I trust the results” is [trustworthy-AI].

Editors:

Andreas HOLZINGER, Human-Centered AI Lab, University of Natural Resources and Life Sciences Vienna, Austria
Katharina KEIBLINGER, Institute of Soil Research, University of Natural Resources and Life Sciences Vienna, Austria
Petr HOLUB, Masayrk University Brno, Czech Republic
Kurt ZATLOUKAL, Diagnostic and Research Center for Molecular Biomedicine, Medical University Graz, Austria
Heimo MUELLER, Information Science & Machine Learning Group, Diagnostics & Research Insitute for Pathology, Medical University Graz

Special issue information:

Keywords: Artificial Intelligence, Biotechnology, Deep Learning, Digital Transformation, Machine Learning
Special Topics: Human-Centered AI (HCAI), Knowledge Extraction (KE), Explainable AI (XAI), Trustworthy AI (TrustAI)
More sample application topics: https://doi.org/10.3390/s22083043

This is a rolling issue. Manuscripts can be submitted until the final deadline. All submissions that pass editorial pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (rolling – as soon as accepted).

Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the corresponding editor for an editorial pre-check (read the Pre-Editorial for a better understanding).

Manuscript submission information:

To have your article considered for this special issue, please submit your manuscript through Editorial Manager at the following link: https://www.editorialmanager.com/nbiot/default1.aspx 

To indicate your article should be included in this special issue, please select the article type ‘VSI: AI & Machine Learning’

Guide for Authors: https://www.elsevier.com/journals/new-biotechnology/1871-6784/guide-for-authors

A sample paper can be seen here: https://doi.org/10.1016/j.nbt.2022.05.002

Why publish in this Special Issue?

  • Special Issue articles are published together on ScienceDirect, making it incredibly easy for other researchers to discover your work.
  • Special content articles are downloaded on ScienceDirect twice as often within the first 24 months than articles published in regular issues.
  • Special content articles attract 20% more citations in the first 24 months than articles published in regular issues.
  • All articles in this special issue will be reviewed by no fewer than two independent experts to ensure the quality, originality and novelty of the work published.

Learn more about the benefits of publishing in a special issue: https://www.elsevier.com/authors/submit-your-paper/special-issues