國立高雄大學圖資館 |

Language: English

Back

Artificial intelligence and machine learning in health care and medical sciencesbest practices and pitfalls /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Artificial intelligence and machine learning in health care and medical sciencesedited by Gyorgy J. Simon, Constantin Aliferis.
Reminder of title:	best practices and pitfalls /
other author:	Simon, Gyorgy J.
Published:	Cham :Springer International Publishing :2024.
Description:	xxvi, 810 p. :ill. (chiefly col.), digital ;24 cm.
Contained By:	Springer Nature eBook
Subject:	Artificial intelligenceMedical applications.
Online resource:	https://doi.org/10.1007/978-3-031-39355-6
ISBN:	9783031393556$q(electronic bk.)

Artificial intelligence and machine learning in health care and medical sciencesbest practices and pitfalls /
Artificial intelligence and machine learning in health care and medical sciencesbest practices and pitfalls /[electronic resource] :edited by Gyorgy J. Simon, Constantin Aliferis. - Cham :Springer International Publishing :2024. - xxvi, 810 p. :ill. (chiefly col.), digital ;24 cm. - Health informatics,2197-3741. - Health informatics..

Predictive Analytics -- Machine Learning -- Artificial Intelligence -- Data Mining -- Clinical Risk Models -- Clinical Risk Stratification -- Data Science -- Causal Discovery -- Causal Inference -- Causal Discovery in Health Sciences -- Causal Inference In Health Sciences -- Ehr Data Analytics -- Medical Knowledge Discovery -- Biomedical Machine Learning -- Biomedical Artificial Intelligence -- Healthcare Machine Learning -- Healthcare Artificial Intelligence -- Translational Science Machine Learning -- Machine Learning for Biological Discovery -- Machine Learning in Bioinformatics -- Machine Learning in Genomics.

Open access.

This open access book provides a detailed review of the latest methods and applications of artificial intelligence (AI) and machine learning (ML) in medicine. With chapters focusing on enabling the reader to develop a thorough understanding of the key concepts in these subject areas along with a range of methods and resulting models that can be utilized to solve healthcare problems, the use of causal and predictive models are comprehensively discussed. Care is taken to systematically describe the concepts to facilitate the reader in developing a thorough conceptual understanding of how different methods and resulting models function and how these relate to their applicability to various issues in health care and medical sciences. Guidance is also given on how to avoid pitfalls that can be encountered on a day-to-day basis and stratify potential clinical risks. Artificial Intelligence and Machine Learning in Health Care and Medical Sciences: Best Practices and Pitfalls is a comprehensive guide to how AI and ML techniques can best be applied in health care. The emphasis placed on how to avoid a variety of pitfalls that can be encountered makes it an indispensable guide for all medical informatics professionals and physicians who utilize these methodologies on a day-to-day basis. Furthermore, this work will be of significant interest to health data scientists, administrators and to students in the health sciences seeking an up-to-date resource on the topic.

ISBN: 9783031393556$q(electronic bk.)

Standard No.: 10.1007/978-3-031-39355-6doiSubjects--Topical Terms:

237917
Artificial intelligence
--Medical applications.

LC Class. No.: R859.7.A78

Dewey Class. No.: 610.285

Artificial intelligence and machine learning in health care and medical sciencesbest practices and pitfalls /
LDR:03265nmm a22003615a 4500 001 665387
003 DE-He213
005 20240321192339.0
006 m d
007 cr nn 008maaau
008 241219s2024 sz s 0 eng d
020 $a 9783031393556$q(electronic bk.)
020 $a 9783031393549$q(paper)
024 7 $a 10.1007/978-3-031-39355-6 $2 doi
035 $a 978-3-031-39355-6
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 MED117000 $2 bisacsh
072 7 $a UXT $2 thema
082 0 4 $a 610.285 $2 23
090 $a R859.7.A78 $b A791 2024
245 0 0 $a Artificial intelligence and machine learning in health care and medical sciences $h [electronic resource] : $b best practices and pitfalls / $c edited by Gyorgy J. Simon, Constantin Aliferis.
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2024.
300 $a xxvi, 810 p. : $b ill. (chiefly col.), digital ; $c 24 cm.
490 1 $a Health informatics, $x 2197-3741
505 0 $a Predictive Analytics -- Machine Learning -- Artificial Intelligence -- Data Mining -- Clinical Risk Models -- Clinical Risk Stratification -- Data Science -- Causal Discovery -- Causal Inference -- Causal Discovery in Health Sciences -- Causal Inference In Health Sciences -- Ehr Data Analytics -- Medical Knowledge Discovery -- Biomedical Machine Learning -- Biomedical Artificial Intelligence -- Healthcare Machine Learning -- Healthcare Artificial Intelligence -- Translational Science Machine Learning -- Machine Learning for Biological Discovery -- Machine Learning in Bioinformatics -- Machine Learning in Genomics.
506 $a Open access.
520 $a This open access book provides a detailed review of the latest methods and applications of artificial intelligence (AI) and machine learning (ML) in medicine. With chapters focusing on enabling the reader to develop a thorough understanding of the key concepts in these subject areas along with a range of methods and resulting models that can be utilized to solve healthcare problems, the use of causal and predictive models are comprehensively discussed. Care is taken to systematically describe the concepts to facilitate the reader in developing a thorough conceptual understanding of how different methods and resulting models function and how these relate to their applicability to various issues in health care and medical sciences. Guidance is also given on how to avoid pitfalls that can be encountered on a day-to-day basis and stratify potential clinical risks. Artificial Intelligence and Machine Learning in Health Care and Medical Sciences: Best Practices and Pitfalls is a comprehensive guide to how AI and ML techniques can best be applied in health care. The emphasis placed on how to avoid a variety of pitfalls that can be encountered makes it an indispensable guide for all medical informatics professionals and physicians who utilize these methodologies on a day-to-day basis. Furthermore, this work will be of significant interest to health data scientists, administrators and to students in the health sciences seeking an up-to-date resource on the topic.
650 0 $a Artificial intelligence $x Medical applications. $3 237917
650 1 4 $a Health Informatics. $3 274212
650 2 4 $a Health Care. $3 913433
650 2 4 $a Bioinformatics. $3 194415
650 2 4 $a Public Health. $3 320661
700 1 $a Simon, Gyorgy J. $3 978201
700 1 $a Aliferis, Constantin F. $3 978202
710 2 $a SpringerLink (Online service) $3 273601
773 0 $t Springer Nature eBook
830 0 $a Health informatics. $3 250132
856 4 0 $u https://doi.org/10.1007/978-3-031-39355-6
950 $a Medicine (SpringerNature-11650)