語系:
繁體中文
English
說明(常見問題)
回圖書館首頁
手機版館藏查詢
登入
回首頁
切換:
標籤
|
MARC模式
|
ISBD
Causation in population health infor...
~
Dammann, Olaf.
FindBook
Google Book
Amazon
博客來
Causation in population health informatics and data science
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Causation in population health informatics and data science/ by Olaf Dammann, Benjamin Smart.
作者:
Dammann, Olaf.
其他作者:
Smart, Benjamin.
出版者:
Cham :Springer International Publishing : : 2019.,
面頁冊數:
ix, 134 p. :ill. (some col.), digital ;24 cm.
內容註:
Introduction -- Data Interpretation -- Data Generation -- Informatics -- Philosophy -- Causal inference -- Knowledge Integration -- Systems Thinking -- Summary and conclusion.
Contained By:
Springer eBooks
標題:
Epidemiology - Data processing. -
電子資源:
https://doi.org/10.1007/978-3-319-96307-5
ISBN:
9783319963075
Causation in population health informatics and data science
Dammann, Olaf.
Causation in population health informatics and data science
[electronic resource] /by Olaf Dammann, Benjamin Smart. - Cham :Springer International Publishing :2019. - ix, 134 p. :ill. (some col.), digital ;24 cm.
Introduction -- Data Interpretation -- Data Generation -- Informatics -- Philosophy -- Causal inference -- Knowledge Integration -- Systems Thinking -- Summary and conclusion.
Marketing text: This book covers the overlap between informatics, computer science, philosophy of causation, and causal inference in epidemiology and population health research. Key concepts covered include how data are generated and interpreted, and how and why concepts in health informatics and the philosophy of science should be integrated in a systems-thinking approach. Furthermore, a formal epistemology for the health sciences and public health is suggested. Causation in Population Health Informatics and Data Science provides a detailed guide of the latest thinking on causal inference in population health informatics. It is therefore a critical resource for all informaticians and epidemiologists interested in the potential benefits of utilising a systems-based approach to causal inference in health informatics.
ISBN: 9783319963075
Standard No.: 10.1007/978-3-319-96307-5doiSubjects--Topical Terms:
3381052
Epidemiology
--Data processing.
LC Class. No.: RA652.2.D38 / D366 2019
Dewey Class. No.: 614.4
Causation in population health informatics and data science
LDR
:02017nmm a2200337 a 4500
001
2177690
003
DE-He213
005
20190604112034.0
006
m d
007
cr nn 008maaau
008
191122s2019 gw s 0 eng d
020
$a
9783319963075
$q
(electronic bk.)
020
$a
9783319963068
$q
(paper)
024
7
$a
10.1007/978-3-319-96307-5
$2
doi
035
$a
978-3-319-96307-5
040
$a
GP
$c
GP
041
0
$a
eng
050
4
$a
RA652.2.D38
$b
D366 2019
072
7
$a
MBG
$2
bicssc
072
7
$a
MED000000
$2
bisacsh
072
7
$a
MBG
$2
thema
072
7
$a
UB
$2
thema
082
0 4
$a
614.4
$2
23
090
$a
RA652.2.D38
$b
D162 2019
100
1
$a
Dammann, Olaf.
$3
3381050
245
1 0
$a
Causation in population health informatics and data science
$h
[electronic resource] /
$c
by Olaf Dammann, Benjamin Smart.
260
$a
Cham :
$b
Springer International Publishing :
$b
Imprint: Springer,
$c
2019.
300
$a
ix, 134 p. :
$b
ill. (some col.), digital ;
$c
24 cm.
505
0
$a
Introduction -- Data Interpretation -- Data Generation -- Informatics -- Philosophy -- Causal inference -- Knowledge Integration -- Systems Thinking -- Summary and conclusion.
520
$a
Marketing text: This book covers the overlap between informatics, computer science, philosophy of causation, and causal inference in epidemiology and population health research. Key concepts covered include how data are generated and interpreted, and how and why concepts in health informatics and the philosophy of science should be integrated in a systems-thinking approach. Furthermore, a formal epistemology for the health sciences and public health is suggested. Causation in Population Health Informatics and Data Science provides a detailed guide of the latest thinking on causal inference in population health informatics. It is therefore a critical resource for all informaticians and epidemiologists interested in the potential benefits of utilising a systems-based approach to causal inference in health informatics.
650
0
$a
Epidemiology
$x
Data processing.
$3
3381052
650
0
$a
Medical informatics.
$3
661258
650
0
$a
Data mining.
$3
562972
650
1 4
$a
Health Informatics.
$3
892928
650
2 4
$a
Logic.
$3
529544
650
2 4
$a
Epidemiology.
$3
568544
700
1
$a
Smart, Benjamin.
$3
3381051
710
2
$a
SpringerLink (Online service)
$3
836513
773
0
$t
Springer eBooks
856
4 0
$u
https://doi.org/10.1007/978-3-319-96307-5
950
$a
Medicine (Springer-11650)
筆 0 讀者評論
館藏地:
全部
電子資源
出版年:
卷號:
館藏
1 筆 • 頁數 1 •
1
條碼號
典藏地名稱
館藏流通類別
資料類型
索書號
使用類型
借閱狀態
預約狀態
備註欄
附件
W9367551
電子資源
11.線上閱覽_V
電子書
EB RA652.2.D38 D366 2019
一般使用(Normal)
在架
0
1 筆 • 頁數 1 •
1
多媒體
評論
新增評論
分享你的心得
Export
取書館
處理中
...
變更密碼
登入