TY - JOUR
T1 - Machine learning for environmental toxicology
T2 - a call for integration and innovation
AU - Miller, Thomas H.
AU - Gallidabino, Matteo D.
AU - Macrae, James I.
AU - Hogstrand, Christer
AU - Bury, Nicolas R.
AU - Barron, Leon P.
AU - Snape, Jason R.
AU - Owen, Stewart F.
PY - 2018/11/20
Y1 - 2018/11/20
N2 - Recent advances in computing power have enabled the application of machine learning (ML) across all areas of science. A step change from a data-rich landscape to one where new hypotheses, relationships, and knowledge is emerging as a result. While ML is related to artificial intelligence (AI), they are not the same. ML is a branch of AI involving the application of statistical algorithms to enable a system to learn. Learning can involve data interpretation, identification of patterns and decision making. However, application and acceptance of ML within environmental toxicology, and more specifically for our viewpoint, environmental risk assessment (ERA), remains low. ML is an example of a disruptive research technology, which is urgently needed to cope with the complexity and scale of work required.
AB - Recent advances in computing power have enabled the application of machine learning (ML) across all areas of science. A step change from a data-rich landscape to one where new hypotheses, relationships, and knowledge is emerging as a result. While ML is related to artificial intelligence (AI), they are not the same. ML is a branch of AI involving the application of statistical algorithms to enable a system to learn. Learning can involve data interpretation, identification of patterns and decision making. However, application and acceptance of ML within environmental toxicology, and more specifically for our viewpoint, environmental risk assessment (ERA), remains low. ML is an example of a disruptive research technology, which is urgently needed to cope with the complexity and scale of work required.
U2 - 10.1021/acs.est.8b05382
DO - 10.1021/acs.est.8b05382
M3 - Article
AN - SCOPUS:85055496550
VL - 52
SP - 12953
EP - 12955
JO - Environmental Science & Technology
JF - Environmental Science & Technology
SN - 0013-936X
IS - 22
ER -