語系:
繁體中文
English
說明(常見問題)
登入
回首頁
切換:
標籤
|
MARC模式
|
ISBD
Secondary Analysis of Electronic Hea...
~
MIT Critical Data.
Secondary Analysis of Electronic Health Records
紀錄類型:
書目-語言資料,印刷品 : Monograph/item
正題名/作者:
Secondary Analysis of Electronic Health Records/ by MIT Critical Data.
作者:
MIT Critical Data.
面頁冊數:
XXI, 427 p. 108 illus., 100 illus. in color.online resource. :
Contained By:
Springer Nature eBook
標題:
Health informatics. -
電子資源:
https://doi.org/10.1007/978-3-319-43742-2
ISBN:
9783319437422
Secondary Analysis of Electronic Health Records
MIT Critical Data.
Secondary Analysis of Electronic Health Records
[electronic resource] /by MIT Critical Data. - 1st ed. 2016. - XXI, 427 p. 108 illus., 100 illus. in color.online resource.
Introduction to the Book -- Objectives of secondary analysis of EHR data -- Review of clinical database -- Challenges and opportunities -- Secondary Analysis of EHR Data Cookbook -- Overview -- Step 1: Formulate research question -- Step 2: Data extraction and preprocessing -- Step 3: Exploratory Analysis -- Step 4: Data analysis -- Step 5: Validation and sensitivity analysis -- Missing Data -- Noise vs. Outliers -- Case Studies -- Introduction -- Predictive Modeling: outcome prediction (discrete) -- Predictive Modeling: dose optimization (regression) -- Pharmacovigilance (classification) -- Comparative effectiveness: propensity score analysis -- Comparative effectiveness: instrumental variable analysis -- Decision and Cost Effectiveness Analysis: Hidden Markov models and Monte Carlo simulation -- Time series analysis: Gaussian processes (ICP modelling) -- Time series analysis: Bayesian inference (Motif discovery in numerical signals) -- Time Series analysis: Optimization techniques for hyperparameter selection -- Signal processing: analysis of waveform data -- Signal processing: False alarm reduction.
Open Access
This book trains the next generation of scientists representing different disciplines to leverage the data generated during routine patient care. It formulates a more complete lexicon of evidence-based recommendations and support shared, ethical decision making by doctors with their patients. Diagnostic and therapeutic technologies continue to evolve rapidly, and both individual practitioners and clinical teams face increasingly complex ethical decisions. Unfortunately, the current state of medical knowledge does not provide the guidance to make the majority of clinical decisions on the basis of evidence. The present research infrastructure is inefficient and frequently produces unreliable results that cannot be replicated. Even randomized controlled trials (RCTs), the traditional gold standards of the research reliability hierarchy, are not without limitations. They can be costly, labor intensive, and slow, and can return results that are seldom generalizable to every patient population. Furthermore, many pertinent but unresolved clinical and medical systems issues do not seem to have attracted the interest of the research enterprise, which has come to focus instead on cellular and molecular investigations and single-agent (e.g., a drug or device) effects. For clinicians, the end result is a bit of a “data desert” when it comes to making decisions. The new research infrastructure proposed in this book will help the medical profession to make ethically sound and well informed decisions for their patients.
ISBN: 9783319437422
Standard No.: 10.1007/978-3-319-43742-2doiSubjects--Topical Terms:
1064466
Health informatics.
LC Class. No.: R858-859.7
Dewey Class. No.: 502.85
Secondary Analysis of Electronic Health Records
LDR
:04058nam a22004335i 4500
001
979477
003
DE-He213
005
20200706082704.0
007
cr nn 008mamaa
008
201211s2016 gw | s |||| 0|eng d
020
$a
9783319437422
$9
978-3-319-43742-2
024
7
$a
10.1007/978-3-319-43742-2
$2
doi
035
$a
978-3-319-43742-2
050
4
$a
R858-859.7
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
502.85
$2
23
100
1
$a
MIT Critical Data.
$e
author.
$4
aut
$4
http://id.loc.gov/vocabulary/relators/aut
$3
1272558
245
1 0
$a
Secondary Analysis of Electronic Health Records
$h
[electronic resource] /
$c
by MIT Critical Data.
250
$a
1st ed. 2016.
264
1
$a
Cham :
$b
Springer International Publishing :
$b
Imprint: Springer,
$c
2016.
300
$a
XXI, 427 p. 108 illus., 100 illus. in color.
$b
online resource.
336
$a
text
$b
txt
$2
rdacontent
337
$a
computer
$b
c
$2
rdamedia
338
$a
online resource
$b
cr
$2
rdacarrier
347
$a
text file
$b
PDF
$2
rda
505
0
$a
Introduction to the Book -- Objectives of secondary analysis of EHR data -- Review of clinical database -- Challenges and opportunities -- Secondary Analysis of EHR Data Cookbook -- Overview -- Step 1: Formulate research question -- Step 2: Data extraction and preprocessing -- Step 3: Exploratory Analysis -- Step 4: Data analysis -- Step 5: Validation and sensitivity analysis -- Missing Data -- Noise vs. Outliers -- Case Studies -- Introduction -- Predictive Modeling: outcome prediction (discrete) -- Predictive Modeling: dose optimization (regression) -- Pharmacovigilance (classification) -- Comparative effectiveness: propensity score analysis -- Comparative effectiveness: instrumental variable analysis -- Decision and Cost Effectiveness Analysis: Hidden Markov models and Monte Carlo simulation -- Time series analysis: Gaussian processes (ICP modelling) -- Time series analysis: Bayesian inference (Motif discovery in numerical signals) -- Time Series analysis: Optimization techniques for hyperparameter selection -- Signal processing: analysis of waveform data -- Signal processing: False alarm reduction.
506
0
$a
Open Access
520
$a
This book trains the next generation of scientists representing different disciplines to leverage the data generated during routine patient care. It formulates a more complete lexicon of evidence-based recommendations and support shared, ethical decision making by doctors with their patients. Diagnostic and therapeutic technologies continue to evolve rapidly, and both individual practitioners and clinical teams face increasingly complex ethical decisions. Unfortunately, the current state of medical knowledge does not provide the guidance to make the majority of clinical decisions on the basis of evidence. The present research infrastructure is inefficient and frequently produces unreliable results that cannot be replicated. Even randomized controlled trials (RCTs), the traditional gold standards of the research reliability hierarchy, are not without limitations. They can be costly, labor intensive, and slow, and can return results that are seldom generalizable to every patient population. Furthermore, many pertinent but unresolved clinical and medical systems issues do not seem to have attracted the interest of the research enterprise, which has come to focus instead on cellular and molecular investigations and single-agent (e.g., a drug or device) effects. For clinicians, the end result is a bit of a “data desert” when it comes to making decisions. The new research infrastructure proposed in this book will help the medical profession to make ethically sound and well informed decisions for their patients.
650
0
$a
Health informatics.
$3
1064466
650
0
$a
Ethics.
$3
555769
650
0
$a
Data mining.
$3
528622
650
0
$a
Statistics .
$3
1253516
650
1 4
$a
Health Informatics.
$3
593963
650
2 4
$a
Data Mining and Knowledge Discovery.
$3
677765
650
2 4
$a
Statistics for Life Sciences, Medicine, Health Sciences.
$3
670172
710
2
$a
SpringerLink (Online service)
$3
593884
773
0
$t
Springer Nature eBook
776
0 8
$i
Printed edition:
$z
9783319437408
776
0 8
$i
Printed edition:
$z
9783319437415
776
0 8
$i
Printed edition:
$z
9783319828992
856
4 0
$u
https://doi.org/10.1007/978-3-319-43742-2
912
$a
ZDB-2-SME
912
$a
ZDB-2-SXM
912
$a
ZDB-2-SOB
950
$a
Medicine (SpringerNature-11650)
950
$a
Medicine (R0) (SpringerNature-43714)
筆 0 讀者評論
多媒體
評論
新增評論
分享你的心得
Export
取書館別
處理中
...
變更密碼[密碼必須為2種組合(英文和數字)及長度為10碼以上]
登入