Life Sciences Biomedical Research Planning for Space Station

1987 ◽  
Author(s):  
Gary R. Primeaux ◽  
Roger Michaud ◽  
Ladonna Miller ◽  
Jim Searcy ◽  
Bernistine Dickey
F1000Research ◽  
2017 ◽  
Vol 6 ◽  
pp. 2012 ◽  
Author(s):  
Hashem Koohy

In the era of explosion in biological data, machine learning techniques are becoming more popular in life sciences, including biology and medicine. This research note examines the rise and fall of the most commonly used machine learning techniques in life sciences over the past three decades.


2014 ◽  
Vol 53 (06) ◽  
pp. 417-418 ◽  
Author(s):  
T. Hothorn

SummaryThis editorial is part of a For-Discussion- Section of Methods of Information in Medicine about the papers “The Evolution of Boosting Algorithms – From Machine Learning to Statistical Modelling” [1] and “Ex-tending Statistical Boosting – An Overview of Recent Methodological Developments” [2], written by Andreas Mayr and co authors. It preludes two discussed reviews on developments and applications of boosting in biomedical research. The two review papers, written by Andreas Mayr, Harald Binder, Olaf Gefeller, and Matthias Schmid, give an overview on recently published methods that utilise gradient or likelihood-based boosting for fitting models in the life sciences. The reviews are followed by invited comments [3] by experts in both boosting theory and applications.


2001 ◽  
Vol 27 (5) ◽  
pp. 1023-1030 ◽  
Author(s):  
V.D. Kern ◽  
S. Bhattacharya ◽  
R.N. Bowman ◽  
F.M. Donovan ◽  
C. Elland ◽  
...  

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