TY  - GEN
N2  - Accurate classification of cancer subtypes based on genomic data is a key component of precision oncology. Subtyping allows for better alignment of therapeutics with the specific biology of an individual patient's tumor. Training predictive models for classification requires collection, sequencing, and labeling of patient samples which incurs significant cost and thus motivates an estimation of the minimum number of samples required to attain a particular classification accuracy. In this work, a minimum sample size estimation strategy for machine learning cancer subtype prediction is developed by combining a subsampling method for learning curve generation with an inverse power law curve fitting method.
DO  - 10.6083/g158bj19x
DO  - DOI
AB  - Accurate classification of cancer subtypes based on genomic data is a key component of precision oncology. Subtyping allows for better alignment of therapeutics with the specific biology of an individual patient's tumor. Training predictive models for classification requires collection, sequencing, and labeling of patient samples which incurs significant cost and thus motivates an estimation of the minimum number of samples required to attain a particular classification accuracy. In this work, a minimum sample size estimation strategy for machine learning cancer subtype prediction is developed by combining a subsampling method for learning curve generation with an inverse power law curve fitting method.
AD  - Oregon Health and Science University
AD  - Oregon Health and Science University
AD  - Oregon Health and Science University
AD  - Oregon Health and Science University
AD  - Oregon Health and Science University
T1  - Machine learning for cancer subtyping: sampling effects on predictive accuracy and feature selection
DA  - 2022-04-21
AU  - Karlberg, Brian
AU  - Lee, Jordan
AU  - Wong, Chris
AU  - Stuart, Josh
AU  - Ellrott, Kyle
L1  - https://digitalcollections.ohsu.edu/record/9633/files/Karlberg_sample_count_abstract_2022-04-20.pdf
PB  - Oregon Health and Science University
PY  - 2022-04-21
ID  - 9633
L4  - https://digitalcollections.ohsu.edu/record/9633/files/Karlberg_sample_count_abstract_2022-04-20.pdf
KW  - Machine Learning
KW  - Neoplasms
KW  - cancer subtypes
KW  - power law curve fitting
KW  - feature engineering
KW  - the cancer genome atlas
KW  - precision oncology
TI  - Machine learning for cancer subtyping: sampling effects on predictive accuracy and feature selection
Y1  - 2022-04-21
L2  - https://digitalcollections.ohsu.edu/record/9633/files/Karlberg_sample_count_abstract_2022-04-20.pdf
LK  - https://digitalcollections.ohsu.edu/record/9633/files/Karlberg_sample_count_abstract_2022-04-20.pdf
UR  - https://digitalcollections.ohsu.edu/record/9633/files/Karlberg_sample_count_abstract_2022-04-20.pdf
ER  -