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019 a| 1396889632a| 1402833157a| 1403850391a| 1409047895a| 1412628918;

020 a| 9783031050718q| (electronic bk.);

020 a| 3031050711q| (electronic bk.);

020 z| 3031050703;

020 z| 9783031050701;

024 7 a| 10.1007/978-3-031-05071-82| doi;

035 a| (Sirsi) o1378429781;

049 a| NEHH;

050 4 a| RC669;

082 04 a| 616.1/200285632| 23/eng/20230515;

245 00 a| AI and big data in cardiology :b| a practical guide /c| Nicolas Duchateau, Andrew P. King, editors.;

260 a| Cham, Switzerland :b| Springer,c| 2023.;

300 a| 1 online resource;

336 a| textb| txt2| rdacontent;

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505 0 a| Introduction -- AI and Machine Learning: the Basics -- From Machine Learning to Deep Learning -- Measurement and Quantification -- Diagnosis -- Outcome Prediction -- Quality Control -- AI and Decision Support -- AI in the Real World -- Analysis of Non-imaging Data -- Conclusions.;

520 a| This book provides a detailed technical overview of the use and applications of artificial intelligence (AI), machine learning and big data in cardiology. Recent technological advancements in these fields mean that there is significant gain to be had in applying these methodologies into day-to-day clinical practice. Chapters feature detailed technical reviews and highlight key current challenges and limitations, along with the available techniques to address them for each topic covered. Sample data sets are also included to provide hands-on tutorials for readers using Python-based Jupyter notebooks, and are based upon real-world examples to ensure the reader can develop their confidence in applying these techniques to solve everyday clinical problems. Artificial Intelligence and Big Data in Cardiology systematically describes and technically reviews the latest applications of AI and big data within cardiology. It is ideal for use by the trainee and practicing cardiologist and informatician seeking an up-to-date resource on the topic with which to aid them in developing a thorough understanding of both basic concepts and recent advances in the field.;

500 a| Includes index.;

588 0 a| Online resource; title from PDF title page (SpringerLink, viewed May 15, 2023).;

650 0 a| Cardiologyx| Data processing.=| ^A1854;

650 0 a| Artificial intelligencex| Medical applications.=| ^A680981;

650 0 a| Big data.=| ^A1157100;

653 a| Internal Medicine;

653 a| Medical;

700 1 a| Duchateau, Nicolas.=| ^A1490429;

700 1 a| King, Andrew P.q| (Andrew Peter)1| https://id.oclc.org/worldcat/entity/E39PCjC77KFvJm7TX4jDDFXDFX=| ^A1489970;

776 08 c| Originalz| 3031050703z| 9783031050701w| (OCoLC)1309870485;

856 40 z| Direct link to eBooku| https://ebookcentral.proquest.com/lib/eastcarolina/detail.action?docID=30611003;

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AI and big data in cardiology : a practical guide / Nicolas Duchateau, Andrew P. King, editors.

Other author	Duchateau, Nicolas.
Other author	King, Andrew P. (Andrew Peter)
Format	Electronic
Publication Info	Cham, Switzerland : Springer, 2023.
Description	1 online resource
Supplemental Content	Direct link to eBook
Subjects	Cardiology--Data processing. Artificial intelligence--Medical applications. Big data.

Contents	Introduction -- AI and Machine Learning: the Basics -- From Machine Learning to Deep Learning -- Measurement and Quantification -- Diagnosis -- Outcome Prediction -- Quality Control -- AI and Decision Support -- AI in the Real World -- Analysis of Non-imaging Data -- Conclusions.
Abstract	This book provides a detailed technical overview of the use and applications of artificial intelligence (AI), machine learning and big data in cardiology. Recent technological advancements in these fields mean that there is significant gain to be had in applying these methodologies into day-to-day clinical practice. Chapters feature detailed technical reviews and highlight key current challenges and limitations, along with the available techniques to address them for each topic covered. Sample data sets are also included to provide hands-on tutorials for readers using Python-based Jupyter notebooks, and are based upon real-world examples to ensure the reader can develop their confidence in applying these techniques to solve everyday clinical problems. Artificial Intelligence and Big Data in Cardiology systematically describes and technically reviews the latest applications of AI and big data within cardiology. It is ideal for use by the trainee and practicing cardiologist and informatician seeking an up-to-date resource on the topic with which to aid them in developing a thorough understanding of both basic concepts and recent advances in the field.
General note	Includes index.
Source of description	Online resource; title from PDF title page (SpringerLink, viewed May 15, 2023).
Issued in other form	Original 3031050703 9783031050701
ISBN	9783031050718 (electronic bk.)
ISBN	3031050711 (electronic bk.)
Standard identifier#	10.1007/978-3-031-05071-8

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AI and big data in cardiology : a practical guide / Nicolas Duchateau, Andrew P. King, editors.

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