Prognostic factor identification from continuous variable by improvement of log-rank test = 로그순위검정의 개선을 통한 연속성 변수로부터의 예후 인자 판별

Cited 0 time in webofscience Cited 0 time in scopus
  • Hit : 125
  • Download : 0
In this research, a prognostic score calculation, “Iterative Patients Partitioning (IPP)” is suggested as an effective method to identify prognostic factor. Prognostic factor can be used in patient survival prediction, drug targets, and disease mechanism study. Due to the limited robustness and sensitivity in previous studies, novel method for evaluating prognostic factor is indispensable. A critical limitation in previous studies is that patients were stratified into different risk groups based on specific threshold of continuous variable. To overcome the specific threshold problem, the Iterative Patients Partitioning that is inspired by the Receiver Operating Characteristic (ROC) curve is presented to consider various cases of risk group stratification based on different thresholds in prognostic factor evaluation. Therefore, the Iterative Patients Partitioning can be applied in the precise identification of prognostic factors.
Advisors
Choi, Chulheeresearcher최철희researcher
Description
한국과학기술원 :바이오및뇌공학과,
Publisher
한국과학기술원
Issue Date
2018
Identifier
325007
Language
eng
Description

학위논문(박사) - 한국과학기술원 : 바이오및뇌공학과, 2018.2,[vii, 159 p. :]

Keywords

Log-rank test▼areceiver operating characteristic curve▼aprognostic factor▼acancer genomics; 로그 순위 검정▼a수신자 조작 특성 곡선▼a예후 지표 인자▼a종양 유전체학

URI
http://hdl.handle.net/10203/264715
Link
http://library.kaist.ac.kr/search/detail/view.do?bibCtrlNo=867893&flag=dissertation
Appears in Collection
BiS-Theses_Ph.D.(박사논문)
Files in This Item
There are no files associated with this item.

qr_code

  • mendeley

    citeulike


rss_1.0 rss_2.0 atom_1.0