AI for life: Trends in artificial intelligence for biotechnology.

Andreas Holzinger, Katharina Keiblinger, Petr Holub, Kurt Zatloukal, Heimo Müller
Author Information
  1. Andreas Holzinger: University of Natural Resources and Life Sciences Vienna, Austria; Medical University Graz, Austria; Alberta Machine Intelligence Institute Edmonton, Canada. Electronic address: andreas.holzinger@boku.ac.at.
  2. Katharina Keiblinger: University of Natural Resources and Life Sciences Vienna, Austria.
  3. Petr Holub: Masaryk University Brno, Czech Republic.
  4. Kurt Zatloukal: Medical University Graz, Austria.
  5. Heimo Müller: Medical University Graz, Austria.

Abstract

Due to popular successes (e.g., ChatGPT) Artificial Intelligence (AI) is on everyone's lips today. When advances in biotechnology are combined with advances in AI unprecedented new potential solutions become available. This can help with many global problems and contribute to important Sustainability Development Goals. Current examples include Food Security, Health and Well-being, Clean Water, Clean Energy, Responsible Consumption and Production, Climate Action, Life below Water, or protect, restore and promote sustainable use of terrestrial ecosystems, sustainably manage forests, combat desertification, and halt and reverse land degradation and halt biodiversity loss. AI is ubiquitous in the life sciences today. Topics include a wide range from machine learning and Big Data analytics, knowledge discovery and data mining, biomedical ontologies, knowledge-based reasoning, natural language processing, decision support and reasoning under uncertainty, temporal and spatial representation and inference, and methodological aspects of explainable AI (XAI) with applications of biotechnology. In this pre-Editorial paper, we provide an overview of open research issues and challenges for each of the topics addressed in this special issue. Potential authors can directly use this as a guideline for developing their paper.

Keywords

MeSH Term

Artificial Intelligence
Biotechnology
Data Mining
Ecosystem
Knowledge Bases

Word Cloud

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