Utilizing Datasets to Advance Perinatal Research. - Wikidata - wikimedia - TriplyDB

Utilizing Datasets to Advance Perinatal Research.

Utilizing Datasets to Advance Perinatal Research.

http://www.wikidata.org/entity/Q38629124

about

Utilizing Datasets to Advance Perinatal Research.

http://www.wikidata.org/entity/Q38629124

description

2017 nî lūn-bûn

@nan

2017年の論文

@ja

2017年論文

@yue

2017年論文

@zh-hant

2017年論文

@zh-hk

2017年論文

@zh-mo

2017年論文

@zh-tw

2017年论文

@wuu

2017年论文

@zh

2017年论文

@zh-cn

name

Utilizing Datasets to Advance Perinatal Research.

@en

type

label

Utilizing Datasets to Advance Perinatal Research.

@en

prefLabel

Utilizing Datasets to Advance Perinatal Research.

@en

P1433

Q38629124-0347E527-90F9-4812-BF2D-4E24783527A5

P1476

Q38629124-01C59D6A-E82D-47F4-9D93-FE62287B015E

P2093

Q38629124-7901967B-366C-45B8-A252-DAE259C61EE4

Q38629124-9393E164-6D45-4F72-A73D-155E0FFF7D8E

Q38629124-BE6115B3-0986-4CD5-9218-CAEFC8DEDBEF

Q38629124-C6B6D560-C486-4BDE-8467-3424F35551A7

P2860

Q38629124-02955EE3-0459-4CCC-BE2F-312023D87D23

Q38629124-033931A7-33D1-41A8-9C01-24A8F44C3E0B

Q38629124-09E7849B-B00A-4392-8123-B2E3F9484B7F

Q38629124-0F011B02-44B2-471B-9CD2-C5B51872A02D

Q38629124-1263908E-79F7-4AB6-8B2F-8B5259F26290

Q38629124-18367A9B-8589-496B-8DF5-827937FFBE7B

Q38629124-1B7BC0E2-F71F-449B-B3D4-F02987A03AFB

Q38629124-29B25A55-5DA7-4654-9EFE-9E47D0027790

Q38629124-2A871F59-778D-49BC-856D-76B62DDD3903

Q38629124-303A4835-A626-45B3-B046-E5D6CD4A7987

P31

Q38629124-2A765FEC-18A1-4ADE-BA6A-B9B88B66F5E1

P356

Q38629124-AE24A3FE-AF4D-458B-A93F-2A69BA75AFEC

P50

Q38629124-52CE15DA-D839-45CB-9404-956565DC83B6

Q38629124-6C02522F-C126-47B1-B4F5-472967CD264B

P577

Q38629124-67A79DD5-B64B-4ED0-BC61-C15F6ABF56E2

P698

Q38629124-5A3E322B-7ED4-4C30-8E3F-68E8F714255F

P932

Q38629124-11DE1FB0-505D-4D94-BC6B-D8B487379537

P356

P1433

Journal of Midwifery & Women's Health

P1476

Utilizing Datasets to Advance Perinatal Research.

@en

P2093

Frances M Biel

http://www.w3.org/2001/XMLSchema#string

Jeremy L Neal

http://www.w3.org/2001/XMLSchema#string

Jonathan M Snowden

http://www.w3.org/2001/XMLSchema#string

Julia C Phillippi

http://www.w3.org/2001/XMLSchema#string

P2860

A scoping review of geographic information systems in maternal health

Causal models and learning from data: integrating causal modeling and statistical estimation

An overview of relations among causal modelling methods

Recent Increases in the U.S. Maternal Mortality Rate: Disentangling Trends From Measurement Issues

Diversity and divergence: the dynamic burden of poor maternal health.

An introduction to causal modeling in clinical trials.

Beyond too little, too late and too much, too soon: a pathway towards evidence-based, respectful maternity care worldwide.

Validation of an online data registry for midwifery practices: a pilot project.

Development and validation of a national data registry for midwife-led births: the Midwives Alliance of North America Statistics Project 2.0 dataset.

Comparative effectiveness research and big data: balancing potential with legal and ethical considerations.

P31

scholarly article

P356

10.1111/JMWH.12640

http://www.w3.org/2001/XMLSchema#string

P50

Nicole S. Carlson

P577

2017-08-11T00:00:00Z

http://www.w3.org/2001/XMLSchema#dateTime

P698

28799702

http://www.w3.org/2001/XMLSchema#string

P932

5808896

http://www.w3.org/2001/XMLSchema#string