Machine Learning in Cardiovascular Medicine (notice n° 1331793)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 02287cam a2200301zu 4500 |
| 003 - CONTROL NUMBER IDENTIFIER | |
| control field | FRCYB88966263 |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20250429184458.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 250429s2020 fr | o|||||0|0|||eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| International Standard Book Number | 9780128202739 |
| 035 ## - SYSTEM CONTROL NUMBER | |
| System control number | FRCYB88966263 |
| 040 ## - CATALOGING SOURCE | |
| Original cataloging agency | FR-PaCSA |
| Language of cataloging | en |
| Transcribing agency | |
| Description conventions | rda |
| 100 1# - MAIN ENTRY--PERSONAL NAME | |
| Personal name | Al'Aref M.D., Subhi J. |
| 245 01 - TITLE STATEMENT | |
| Title | Machine Learning in Cardiovascular Medicine |
| Statement of responsibility, etc. | ["Al'Aref M.D., Subhi J.", 'Singh, Gurpreet', 'Baskaran, Lohendran'] |
| 264 #1 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE | |
| Name of producer, publisher, distributor, manufacturer | Academic Press |
| Date of production, publication, distribution, manufacture, or copyright notice | 2020 |
| 300 ## - PHYSICAL DESCRIPTION | |
| Extent | p. |
| 336 ## - CONTENT TYPE | |
| Content type code | txt |
| Source | rdacontent |
| 337 ## - MEDIA TYPE | |
| Media type code | c |
| Source | rdamdedia |
| 338 ## - CARRIER TYPE | |
| Carrier type code | c |
| Source | rdacarrier |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc. | Machine Learning in Cardiovascular Medicine addresses the ever-expanding applications of artificial intelligence (AI), specifically machine learning (ML), in healthcare and within cardiovascular medicine. The book focuses on emphasizing ML for biomedical applications and provides a comprehensive summary of the past and present of AI, basics of ML, and clinical applications of ML within cardiovascular medicine for predictive analytics and precision medicine. It helps readers understand how ML works along with its limitations and strengths, such that they can could harness its computational power to streamline workflow and improve patient care. It is suitable for both clinicians and engineers; providing a template for clinicians to understand areas of application of machine learning within cardiovascular research; and assist computer scientists and engineers in evaluating current and future impact of machine learning on cardiovascular medicine. - Provides an overview of machine learning, both for a clinical and engineering audience - Summarize recent advances in both cardiovascular medicine and artificial intelligence - Discusses the advantages of using machine learning for outcomes research and image processing - Addresses the ever-expanding application of this novel technology and discusses some of the unique challenges associated with such an approach |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name entry element | |
| 700 0# - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Al'Aref M.D., Subhi J. |
| 700 0# - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Singh, Gurpreet |
| 700 0# - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Baskaran, Lohendran |
| 856 40 - ELECTRONIC LOCATION AND ACCESS | |
| Access method | Cyberlibris |
| Uniform Resource Identifier | <a href="https://international.scholarvox.com/netsen/book/88966263">https://international.scholarvox.com/netsen/book/88966263</a> |
| Electronic format type | text/html |
| Host name | |
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