東華大學圖書館 |

Language: English

Help

回圖書館首頁

手機版館藏查詢

Back

Switch To: Labeled | MARC Mode | ISBD

Clinical applications of artificial ...

Asselbergs, Folkert W.

Linked to FindBook

Google Book

Amazon

博客來

Clinical applications of artificial intelligence in real-world data

Record Type:	Electronic resources : Monograph/item
Title/Author:	Clinical applications of artificial intelligence in real-world data/ edited by Folkert W. Asselbergs ... [et al.].
other author:	Asselbergs, Folkert W.
Published:	Cham :Springer International Publishing : : 2023.,
Description:	vi, 285 p. :ill., digital ;24 cm.
[NT 15003449]:	Part 1: Data Processing, Storage, Regulations -- Biomedical Big Data: Opportunities and Challenges -- Quality Control, Data Cleaning, Imputation -- Data Security And Privacy Issues -- Data Standards and Terminology -- Biomedical Ontologies -- Graph Databases as Future Of Data Storage -- Data Integration, Harmonization -- Natural Language Processing And Text Mining- Turning Unstructured Data Into Structured -- Part 2: Analytics -- Statistical Analysis Statistical Analysis - Causality, Mendelian Randomization -- Statistical Analysis - Meta-Analysis/Reproducibility -- Machine Learning - Basic Concepts -- Machine Learning - Basic Supervised Methods -- Machine Learning - Basic Unsupervised Methods -- Machine Learning - Evaluation -- Machine Learning - Representation Learning/Feature Selection/Engineering -- Machine Learning - Interpretation -- Deep Learning - Prediction -- Deep Learning - Autoencoders -- Artificial Intelligence -- Machine Learning In Practice - Clinical Decision Support, Risk Prediction, Diagnosis -- Machine Learning In Practice - Evaluation Clinical Value, Guidelines -- Challenges Of Machine Learning and AI.
Contained By:	Springer Nature eBook
Subject:	Artificial intelligence - Medical applications. -
Online resource:	https://doi.org/10.1007/978-3-031-36678-9
ISBN:	9783031366789

Clinical applications of artificial intelligence in real-world data
Clinical applications of artificial intelligence in real-world data[electronic resource] /edited by Folkert W. Asselbergs ... [et al.]. - Cham :Springer International Publishing :2023. - vi, 285 p. :ill., digital ;24 cm.

Part 1: Data Processing, Storage, Regulations -- Biomedical Big Data: Opportunities and Challenges -- Quality Control, Data Cleaning, Imputation -- Data Security And Privacy Issues -- Data Standards and Terminology -- Biomedical Ontologies -- Graph Databases as Future Of Data Storage -- Data Integration, Harmonization -- Natural Language Processing And Text Mining- Turning Unstructured Data Into Structured -- Part 2: Analytics -- Statistical Analysis Statistical Analysis - Causality, Mendelian Randomization -- Statistical Analysis - Meta-Analysis/Reproducibility -- Machine Learning - Basic Concepts -- Machine Learning - Basic Supervised Methods -- Machine Learning - Basic Unsupervised Methods -- Machine Learning - Evaluation -- Machine Learning - Representation Learning/Feature Selection/Engineering -- Machine Learning - Interpretation -- Deep Learning - Prediction -- Deep Learning - Autoencoders -- Artificial Intelligence -- Machine Learning In Practice - Clinical Decision Support, Risk Prediction, Diagnosis -- Machine Learning In Practice - Evaluation Clinical Value, Guidelines -- Challenges Of Machine Learning and AI.

This book is a thorough and comprehensive guide to the use of modern data science within health care. Critical to this is the use of big data and its analytical potential to obtain clinical insight into issues that would otherwise have been missed and is central to the application of artificial intelligence. It therefore has numerous uses from diagnosis to treatment. Clinical Applications of Artificial Intelligence in Real-World Data is a critical resource for anyone interested in the use and application of data science within medicine, whether that be researchers in medical data science or clinicians looking for insight into the use of these techniques.

ISBN: 9783031366789

Standard No.: 10.1007/978-3-031-36678-9doiSubjects--Topical Terms:

900591
Artificial intelligence
--Medical applications.

LC Class. No.: R859.7.A78

Dewey Class. No.: 610.28563

Clinical applications of artificial intelligence in real-world data
LDR:02828nmm a2200337 a 4500 001 2335697
003 DE-He213
005 20231104054643.0
006 m d
007 cr nn 008maaau
008 240402s2023 sz s 0 eng d
020 $a 9783031366789 $q (electronic bk.)
020 $a 9783031366772 $q (paper)
024 7 $a 10.1007/978-3-031-36678-9 $2 doi
035 $a 978-3-031-36678-9
040 $a GP $c GP
041 0 $a eng
050 4 $a R859.7.A78
072 7 $a MBG $2 bicssc
072 7 $a UB $2 bicssc
072 7 $a MED000000 $2 bisacsh
072 7 $a UXT $2 thema
082 0 4 $a 610.28563 $2 23
090 $a R859.7.A78 $b C641 2023
245 0 0 $a Clinical applications of artificial intelligence in real-world data $h [electronic resource] / $c edited by Folkert W. Asselbergs ... [et al.].
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2023.
300 $a vi, 285 p. : $b ill., digital ; $c 24 cm.
505 0 $a Part 1: Data Processing, Storage, Regulations -- Biomedical Big Data: Opportunities and Challenges -- Quality Control, Data Cleaning, Imputation -- Data Security And Privacy Issues -- Data Standards and Terminology -- Biomedical Ontologies -- Graph Databases as Future Of Data Storage -- Data Integration, Harmonization -- Natural Language Processing And Text Mining- Turning Unstructured Data Into Structured -- Part 2: Analytics -- Statistical Analysis Statistical Analysis - Causality, Mendelian Randomization -- Statistical Analysis - Meta-Analysis/Reproducibility -- Machine Learning - Basic Concepts -- Machine Learning - Basic Supervised Methods -- Machine Learning - Basic Unsupervised Methods -- Machine Learning - Evaluation -- Machine Learning - Representation Learning/Feature Selection/Engineering -- Machine Learning - Interpretation -- Deep Learning - Prediction -- Deep Learning - Autoencoders -- Artificial Intelligence -- Machine Learning In Practice - Clinical Decision Support, Risk Prediction, Diagnosis -- Machine Learning In Practice - Evaluation Clinical Value, Guidelines -- Challenges Of Machine Learning and AI.
520 $a This book is a thorough and comprehensive guide to the use of modern data science within health care. Critical to this is the use of big data and its analytical potential to obtain clinical insight into issues that would otherwise have been missed and is central to the application of artificial intelligence. It therefore has numerous uses from diagnosis to treatment. Clinical Applications of Artificial Intelligence in Real-World Data is a critical resource for anyone interested in the use and application of data science within medicine, whether that be researchers in medical data science or clinicians looking for insight into the use of these techniques.
650 0 $a Artificial intelligence $x Medical applications. $3 900591
650 0 $a Medicine $x Data processing. $3 661309
650 0 $a Big data. $3 2045508
650 1 4 $a Health Informatics. $3 892928
650 2 4 $a Health Care. $3 3538867
650 2 4 $a Bioinformatics. $3 553671
650 2 4 $a Big Data. $3 3134868
700 1 $a Asselbergs, Folkert W. $3 3668291
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer Nature eBook
856 4 0 $u https://doi.org/10.1007/978-3-031-36678-9
950 $a Medicine (SpringerNature-11650)