AI for life: Trends in artificial intelligence for biotechnology

被引:172
作者
Holzinger, Andreas [1 ,2 ,4 ]
Keiblingera, Katharina [1 ]
Holub, Petr [3 ]
Zatloukal, Kurt [2 ]
Mueller, Heimo [2 ]
机构
[1] Univ Nat Resources & Life Sci Vienna, Vienna, Austria
[2] Med Univ Graz, Graz, Austria
[3] Masaryk Univ Brno, Brno, Czech Republic
[4] Alberta Machine Intelligence Inst Edmonton, Edmonton, AB, Canada
基金
奥地利科学基金会;
关键词
Artificial Intelligence; Biotechnology; Deep Learning; Digital Transformation; Machine Learning; STANDARDS;
D O I
10.1016/j.nbt.2023.02.001
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
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.
引用
收藏
页码:16 / 24
页数:9
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