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Lessons Learned in Replicating Data-Driven Experiments in Multiple Medical Systems and Patient Populations 1 Stevens Samantha Kleinberg, PhD1 and No´emie Elhadad, PhD2
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City

Seattle / Austin / New York City / Hoboken / /

Company

Cambridge University Press / Geisinger / Multiple Medical Systems / Wilson / Case / /

Country

Columbia / /

Currency

CHF / /

Facility

American College of Cardiology / PhD2 Institute of Technology / Columbia University Medical Center / Columbia University / /

IndustryTerm

post-processing step / semantic / data mining / healthcare / computational tools / hospital systems / medical systems / healthcare process / natural language processing / mining / /

MedicalCondition

Osteoarthrosis / dx_hypothyroidism / Essential hypertension / dx_COPD_asthma / progressive illness / COPD asthma / chronic kidney disease / Disorder / angina / allied disorders / illness / thyroid dysfunction / dx_diabetes / congestive heart failure / hypertension / disease / hypothyroidism / soft tissues Diseases / progressive disease / diabetes / Other disorders / lung cancer / heart failure / diseases / dx_angina / AIDS / back Other disorders / unspecified disorders / Disorders / /

Organization

Cambridge University / National Science Foundation / American Statistical Association / Columbia University / New York / Am Med Inform Assoc / vol. / Cases Controls Lab / Columbia University Medical Center / Institute of Technology / the American College / Computing Research Association for the CIFellows / /

Person

Stewart / Shah / Roy / /

Position

General / Major / representative / involving head / /

Product

ICD9 / rela / Azithromycin / /

ProvinceOrState

New York / Pennsylvania / /

PublishedMedium

Clinical Medicine / Journal of the American Statistical Association / Critical Care Medicine / Lecture Notes in Computer Science / /

Technology

Genomics / machine learning / natural language processing / data mining / Simulation / /

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