J 2023

AI for Life: Trends in Artificial Intelligence for Biotechnology

HOLZINGER, Andreas, Katharina KEIBLINGER, Petr HOLUB, Kurt ZATLOUKAL, Heimo MÜLLER et. al.

Basic information

Original name

AI for Life: Trends in Artificial Intelligence for Biotechnology

Authors

HOLZINGER, Andreas, Katharina KEIBLINGER, Petr HOLUB (203 Czech Republic, guarantor, belonging to the institution), Kurt ZATLOUKAL and Heimo MÜLLER

Edition

NEW BIOTECHNOLOGY, NETHERLANDS, ELSEVIER, 2023, 1871-6784

Other information

Language

English

Type of outcome

Článek v odborném periodiku

Field of Study

10201 Computer sciences, information science, bioinformatics

Country of publisher

Germany

Confidentiality degree

není předmětem státního či obchodního tajemství

References:

Impact factor

Impact factor: 5.400 in 2022

RIV identification code

RIV/00216224:14610/23:00130298

Organization unit

Institute of Computer Science

UT WoS

000936300300001

Keywords in English

AI; biotechology; explainable artificial intelligence; XAI; life sciences; provenance
Změněno: 20/3/2024 17:20, doc. RNDr. Petr Holub, Ph.D.

Abstract

V originále

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.

Links

101079183, interní kód MU
Name: BioMedAI TWINNING
Investor: European Union, Widening participation and strengthening the European Research Area