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Research article summary:
Machine learning for sub-population assessment: evaluating the C-section rate of different physician practices.
Abstract Extract:
We apply machine learning to the problem of subpopulation assessment for Caesarian Section. In subpopulation assessment, we are interested in making predictions not for a single patient, but for groups of patients. Typically, in any large population, ... (Full abstract text below) Published 2002
in Journal: Proc AMIA Symp
(Language : eng)
Full Pubmed Extract
This information was retrieved, real-time, on your behalf from the public area of the Pubmed website:
1. Proc AMIA Symp.
2002 ;():126-30
Machine learning for sub-population assessment: evaluating the C-section rate of different physician practices.
Caruana R, Niculescu RS, Rao RB, Simms C
Cornell University, Computer Science, Ithaca, NY, USA.
We apply machine learning to the problem of subpopulation assessment for Caesarian Section. In subpopulation assessment, we are interested in making predictions not for a single patient, but for groups of patients. Typically, in any large population, different subpopulations will have different "outcome" rates. In our example, the C-section rate of a population of 22,176 expectant mothers is 16.8%; yet, the 17 physician groups that serve this population have vastly different group C-section rates, ranging from 11% to 23%. The ultimate goal of subpopulation assessment is to determine if these variations in the observed rates can be attributed to (a) variations in intrinsic risk of the patient sub-populations (i.e. some groups contain more "high-risk C-section" patients), or (b) differences in physician practice (i.e. some groups do more C-sections). Our results indicate that although there is some variation in intrinsic risk, there is also much variation in physician practice.
PMID : 12463800 [PubMed - Indexed for MEDLINE]
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Full Author Information
| First Name | LastName | Initials |
| Rich | Caruana | R |
| Radu S | Niculescu | RS |
| R Bharat | Rao | RB |
| Cynthia | Simms | C |
Affiliation: Cornell University, Computer Science, Ithaca, NY, USA.
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Category links from this article:- Artificial Intelligence
- Cesarean Section - statistics & numerical data
- Data Interpretation, Statistical
- Decision Trees
- Female
- Humans
- Neural Networks (Computer)
- Physician's Practice Patterns - statistics & numerical data
- Pregnancy
| | Related Memletics topics: |
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