|
|
|
|
| LEADER |
03636nmm a2200601 u 4500 |
| 001 |
EB002174661 |
| 003 |
EBX01000000000000001312438 |
| 005 |
00000000000000.0 |
| 007 |
cr||||||||||||||||||||| |
| 008 |
230908 ||| eng |
| 020 |
|
|
|a 9781000885095
|
| 020 |
|
|
|a 9781000885163
|
| 020 |
|
|
|a 9781003226642
|
| 020 |
|
|
|a 1000885097
|
| 020 |
|
|
|a 100088516X
|
| 020 |
|
|
|a 1003226647
|
| 050 |
|
4 |
|a Q180.55.E4
|
| 100 |
1 |
|
|a Hastings, Janna
|
| 245 |
0 |
0 |
|a AI for scientific discovery
|c Janna Hastings
|
| 246 |
3 |
1 |
|a Artificial intelligence for scientific discovery
|
| 250 |
|
|
|a First edition
|
| 260 |
|
|
|a Boca Raton, FL
|b CRC Press
|c 2023
|
| 300 |
|
|
|a xiii, 119 pages
|b illustrations
|
| 505 |
0 |
|
|a Introduction : AI and the digital revolution in science -- AI for managing scientific literature and evidence -- AI for data interpretation -- AI for reproducible research -- Limitations of AI and strategies for combating bias -- Conclusion : AI and the future of scientific discovery
|
| 505 |
0 |
|
|a Includes bibliographical references and index
|
| 653 |
|
|
|a COMPUTERS / Computer Science / bisacsh
|
| 653 |
|
|
|a Artificial intelligence / fast
|
| 653 |
|
|
|a Artificial intelligence / http://id.loc.gov/authorities/subjects/sh85008180
|
| 653 |
|
|
|a Science / Data processing / http://id.loc.gov/authorities/subjects/sh85118562
|
| 653 |
|
|
|a Intelligence artificielle
|
| 653 |
|
|
|a COMPUTERS / Social Aspects / General / bisacsh
|
| 653 |
|
|
|a Research / Data processing / http://id.loc.gov/authorities/subjects/sh85113022
|
| 653 |
|
|
|a artificial intelligence / aat
|
| 653 |
|
|
|a Science / Data processing / fast
|
| 653 |
|
|
|a COMPUTERS / General / bisacsh
|
| 653 |
|
|
|a Sciences / Informatique
|
| 653 |
|
|
|a Research / Data processing / fast
|
| 041 |
0 |
7 |
|a eng
|2 ISO 639-2
|
| 989 |
|
|
|b OREILLY
|a O'Reilly
|
| 490 |
0 |
|
|a AI for everything series
|
| 028 |
5 |
0 |
|a 10.1201/9781003226642
|
| 776 |
|
|
|z 9781032124841
|
| 776 |
|
|
|z 9781032128771
|
| 776 |
|
|
|z 1000885097
|
| 776 |
|
|
|z 100088516X
|
| 776 |
|
|
|z 9781003226642
|
| 776 |
|
|
|z 1003226647
|
| 776 |
|
|
|z 9781000885163
|
| 776 |
|
|
|z 9781000885095
|
| 856 |
4 |
0 |
|u https://learning.oreilly.com/library/view/~/9781000885163/?ar
|x Verlag
|3 Volltext
|
| 082 |
0 |
|
|a 006.3
|
| 082 |
0 |
|
|a 500
|
| 520 |
|
|
|a "AI for Scientific Discovery provides an accessible introduction to the wide-ranging applications of artificial intelligence technologies in scientific research and discovery across the full breadth of scientific disciplines. Artificial intelligence technologies support discovery science in multiple different ways. They support literature management and synthesis, allowing the wealth of what has already been discovered and reported on to be integrated and easily accessed. They play a central role in data analysis and interpretation - in the context of what is called 'data science'. AI is also helping to combat the reproducibility crisis in scientific research, by underpinning the discovery process with AI-enabled standards and pipelines, support the management of large-scale data and knowledge resources so that they can be shared, integrated and serve as a background 'knowledge ecosystem' into which new discoveries can be embedded. However, there are limitations to what AI can achieve and its outputs can be biased and confounded thus should not be blindly trusted. The latest generation of hybrid and 'human-in-the-loop' AI technologies have as their objective a balance between human inputs and insights and the power of the number-crunching and statistical inference at massive scale that AI technologies are best at"--
|