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| 001 | 141135 | ||
| 005 | 20240229105119.0 | ||
| 024 | 7 | _ | |a 10.1109/MPUL.2018.2857226 |2 doi |
| 024 | 7 | _ | |a pmid:30273136 |2 pmid |
| 024 | 7 | _ | |a 2154-2287 |2 ISSN |
| 024 | 7 | _ | |a 2154-2317 |2 ISSN |
| 024 | 7 | _ | |a altmetric:70395558 |2 altmetric |
| 037 | _ | _ | |a DKFZ-2018-01666 |
| 041 | _ | _ | |a eng |
| 082 | _ | _ | |a 570 |
| 100 | 1 | _ | |a Mandal, Subhamoy |0 P:(DE-HGF)0 |b 0 |e First author |
| 245 | _ | _ | |a Imaging Intelligence: AI Is Transforming Medical Imaging Across the Imaging Spectrum. |
| 260 | _ | _ | |a New York, NY |c 2018 |b IEEE |
| 336 | 7 | _ | |a article |2 DRIVER |
| 336 | 7 | _ | |a Output Types/Journal article |2 DataCite |
| 336 | 7 | _ | |a Journal Article |b journal |m journal |0 PUB:(DE-HGF)16 |s 1540556696_23542 |2 PUB:(DE-HGF) |
| 336 | 7 | _ | |a ARTICLE |2 BibTeX |
| 336 | 7 | _ | |a JOURNAL_ARTICLE |2 ORCID |
| 336 | 7 | _ | |a Journal Article |0 0 |2 EndNote |
| 520 | _ | _ | |a Artificial intelligence (AI) and machine learning (ML) have influenced medicine in myriad ways, and medical imaging is at the forefront of technological transformation. Recent advances in AI/ML fields have made an impact on imaging and image analysis across the board, from microscopy to radiology. AI has been an active field of research since the 1950s; however, for most of this period, algorithms achieved subhuman performance and were not broadly adopted in medicine. Recent enhancements for computational hardware is enabling researchers to revisit old AI algorithms and experiment with new mathematical ideas. Researchers are applying these methods to a broad array of medical technologies, ranging from microscopic image analysis to tomographic image reconstruction and diagnostic planning. |
| 536 | _ | _ | |a 315 - Imaging and radiooncology (POF3-315) |0 G:(DE-HGF)POF3-315 |c POF3-315 |f POF III |x 0 |
| 588 | _ | _ | |a Dataset connected to CrossRef, PubMed, |
| 700 | 1 | _ | |a Greenblatt, Aaron B |b 1 |
| 700 | 1 | _ | |a An, Jingzhi |b 2 |
| 773 | _ | _ | |a 10.1109/MPUL.2018.2857226 |g Vol. 9, no. 5, p. 16 - 24 |0 PERI:(DE-600)2563701-0 |n 5 |p 16 - 24 |t IEEE pulse |v 9 |y 2018 |x 2154-2317 |
| 909 | C | O | |o oai:inrepo02.dkfz.de:141135 |p VDB |
| 910 | 1 | _ | |a Deutsches Krebsforschungszentrum |0 I:(DE-588b)2036810-0 |k DKFZ |b 0 |6 P:(DE-HGF)0 |
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| 914 | 1 | _ | |y 2018 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0300 |2 StatID |b Medline |
| 915 | _ | _ | |a JCR |0 StatID:(DE-HGF)0100 |2 StatID |b IEEE PULSE : 2017 |
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| 920 | 1 | _ | |0 I:(DE-He78)E020-20160331 |k E020 |l Medizinische Physik in der Radiologie |x 0 |
| 980 | _ | _ | |a journal |
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| 980 | _ | _ | |a I:(DE-He78)E020-20160331 |
| 980 | _ | _ | |a UNRESTRICTED |
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