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Physical Sciences and Mathematics Commons™
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Full-Text Articles in Physical Sciences and Mathematics
Biogeographical Patterns Of Soil Microbial Communities: Ecological, Structural, And Functional Diversity And Their Application To Soil Provenance, Natalie Damaso
FIU Electronic Theses and Dissertations
The current ecological hypothesis states that the soil type (e.g., chemical and physical properties) determines which microbes occupy a particular soil and provides the foundation for soil provenance studies. As human profiles are used to determine a match between evidence from a crime scene and a suspect, a soil microbial profile can be used to determine a match between soil found on the suspect’s shoes or clothing to the soil at a crime scene. However, for a robust tool to be applied in forensic application, an understanding of the uncertainty associated with any comparisons and the parameters that can significantly …
Online Cross-Validation-Based Ensemble Learning, David Benkeser, Samuel D. Lendle, Cheng Ju, Mark J. Van Der Laan
Online Cross-Validation-Based Ensemble Learning, David Benkeser, Samuel D. Lendle, Cheng Ju, Mark J. Van Der Laan
U.C. Berkeley Division of Biostatistics Working Paper Series
Online estimators update a current estimate with a new incoming batch of data without having to revisit past data thereby providing streaming estimates that are scalable to big data. We develop flexible, ensemble-based online estimators of an infinite-dimensional target parameter, such as a regression function, in the setting where data are generated sequentially by a common conditional data distribution given summary measures of the past. This setting encompasses a wide range of time-series models and as special case, models for independent and identically distributed data. Our estimator considers a large library of candidate online estimators and uses online cross-validation to …
Privacy And Accountability In Black-Box Medicine, Roger Allan Ford, W. Nicholson Price Ii
Privacy And Accountability In Black-Box Medicine, Roger Allan Ford, W. Nicholson Price Ii
Law Faculty Scholarship
Black-box medicine—the use of big data and sophisticated machine learning techniques for health-care applications—could be the future of personalized medicine. Black-box medicine promises to make it easier to diagnose rare diseases and conditions, identify the most promising treatments, and allocate scarce resources among different patients. But to succeed, it must overcome two separate, but related, problems: patient privacy and algorithmic accountability. Privacy is a problem because researchers need access to huge amounts of patient health information to generate useful medical predictions. And accountability is a problem because black-box algorithms must be verified by outsiders to ensure they are accurate and …