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Skip to Search Results- 28Greiner, Russell (Computing Science)
- 2Schuurmans, Dale (Computing Science)
- 1Bolduc, Francois (Pediatrics)
- 1Brown, Matthew (Psychiatry)
- 1Brown, Matthew R.G. (Psychiatry)
- 1Bulitko, Vadim (Computing Science)
- 2Wen, Junfeng
- 1Allen, Felicity R
- 1Bastani, Meysam
- 1Borle, Neil C
- 1Bostan, Babak
- 1Davis, Sarah (Sacha) Maren
- 8Machine learning
- 7Machine Learning
- 2Diagnosis
- 2Fmri
- 2Functional magnetic resonance imaging
- 2Schizophrenia
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Fall 2009
Understanding biochemical reactions inside cells of individual organisms is a key factor for improving our biological knowledge. Signaling pathways provide a road map for a wide range of these chemical reactions that convert one signal or stimulus into another. In general, each signaling pathway...
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Fall 2009
This thesis addresses the challenge of prognosis, in terms of survival prediction, for patients with Glioblastoma Multiforme brain tumors. Glioblastoma is the most malignant brain tumor, which has a median survival time of no more than a year. Accurate assessment of prognostic factors is critical...
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Fall 2009
In this thesis we consider the task of catching a moving target with multiple pursuers, also known as the “Pursuit Game”, in which coordination among the pursuers is critical. Our testbed is inspired by the pursuit problem in video games, which require fast planning to guarantee fluid frame...
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Spring 2010
This thesis presents Pathway Informed Analysis (PIA), a classification method for predicting disease states (diagnosis) from metabolic profile measurements that incorporates biological knowledge in the form of metabolic pathways. A metabolic pathway describes a set of chemical reactions that...
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Spring 2011
Standard survival analysis focuses on population-based studies. The objective of our work, survival prediction, is different: to find the most accurate model for predicting the survival times for each individual patient. We view this as a regression problem, where we try to map the features for...
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Fall 2012
Functional Magnetic Resonance Imaging (fMRI) measures the dynamic activity of each voxel of a brain. This dissertation addresses the challenge of learning a diagnostic classifier that uses a subject’s fMRI data to distinguish subjects with neuropsychiatric disorders from healthy controls. fMRI...
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Spring 2013
Many machine learning algorithms learn from the data by capturing certain interesting characteristics. Decision trees are used in many classification tasks. In some circumstances, we only want to consider fixed-depth trees. Unfortunately, finding the optimal depth-d decision tree can require time...
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Fall 2013
Many learning situations involve learning the conditional distribution $p(y|x)$ when the training data is drawn from the training distribution $p{tr}(x)$, even though it will later be used to predict for instances drawn from a different test distribution $p{te}(x)$. Most current approaches focus...
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Assessing the Feasibility of Learning Biomedical Phenotype Patterns Using High-Throughput Omics Profiles
DownloadSpring 2014
A decade after the completion of the human genome project, the rapid advancement of the high-throughput measurement technologies has made omics (genomics, epigenomics, transcriptomics, metabolomics) profiling feasible. The availability of such omics profiles has raised the hope for the...
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Spring 2014
Each patient with Type-1 diabetes must decide how much insulin to inject before each meal to maintain an acceptable level of blood glucose. The actual injection dose is based on a formula that takes current blood glucose level and the meal size into consideration. While following this insulin...