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Tìm được 6 kết quả
A Review of Current Machine Learning Methods Used for Cancer Recurrence Modeling and Prediction [electronic resource]
Tác giả:
Xuất bản: Los Alamos NM Oak Ridge Tenn: Los Alamos National Laboratory Distributed by the Office of Scientific and Technical Information US Dept of Energy, 2016
Bộ sưu tập: Metadata
ddc:  571.6
 
Mathematical modeling of within-host Zika virus dynamics [electronic resource]
Tác giả:
Xuất bản: Los Alamos NM Oak Ridge Tenn: Los Alamos National Laboratory Distributed by the Office of Scientific and Technical Information US Dept of Energy, 2018
Bộ sưu tập: Metadata
ddc:  610.6
 
Modeling HCV cure after an ultra-short duration of therapy with direct acting agents [electronic resource]
Tác giả:
Xuất bản: Los Alamos NM Oak Ridge Tenn: Los Alamos National Laboratory Distributed by the Office of Scientific and Technical Information US Dept of Energy, 2017
Bộ sưu tập: Metadata
ddc:  571.6
 
Large-scale Epidemic Modeling and Simulation [electronic resource] : W14_EpiSim Institutional Computing Project
Tác giả:
Xuất bản: Los Alamos NM Oak Ridge Tenn: Los Alamos National Laboratory Distributed by the Office of Scientific and Technical Information US Dept of Energy, 2016
Bộ sưu tập: Metadata
ddc:  630.9
 
Mathematical Modeling of Hepatitis C Prevalence Reduction with Antiviral Treatment Scale-Up in Persons Who Inject Drugs in Metropolitan Chicago [electronic resource]
Tác giả:
Xuất bản: Los Alamos NM Oak Ridge Tenn: Los Alamos National Laboratory Distributed by the Office of Scientific and Technical Information US Dept of Energy, 2015
Bộ sưu tập: Metadata
ddc:  576.
 
Sustained virological response with intravenous silibinin [electronic resource] : individualized IFN-free therapy via re...
Tác giả:
Xuất bản: Los Alamos NM Oak Ridge Tenn: Los Alamos National Laboratory Distributed by the Office of Scientific and Technical Information US Dept of Energy, 2014
Bộ sưu tập: Metadata
ddc:  572.6
 
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