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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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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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Spring 2021
This dissertation demonstrates how to utilize data collected previously from different sources to facilitate learning and inference for a target task. Learning from scratch for a target task or environment can be expensive and time-consuming. To address this problem, we make three contributions...
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Building an expert-system based conversational agent to provide personalised resources about neurological disorders
DownloadSpring 2022
Researchers developing artificially intelligent conversational agents (aka, chat- bots) seek effective ways to provide personal assistance to users with various needs. We have implemented a web-based conversational agent that recom- mends resources to help clients (caregivers of patients...
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Spring 2020
Mapping the macrostructural connectivity of the living human brain is one of the primary goals of neuroscientists who study connectomics. The reconstruction of a brain's structural connectivity, aka its connectome, typically involves applying expert analysis to diffusion-weighted magnetic...
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Spring 2016
One of the key obstacles to the effective use of mass spectrometry (MS) in high throughput metabolomics is the difficulty in interpreting measured spectra to accurately and efficiently identify metabolites. Traditional methods for automated metabolite identification compare the target MS spectrum...
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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 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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Learning Individual Readmission-Free Survival Distributions using Longitudinal Medical Events
DownloadFall 2023
The rate of 30-day hospital readmission is a common measurement of hospital quality, which can affect the funding a hospital receives. Over a quarter of readmissions are estimated to be preventable with adequate interventions, but these interventions are themselves costly. For this reason, many...
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Spring 2018
Patients with Type I Diabetes (T1D) must take insulin injections to prevent the serious long term effects of hyperglycemia â high blood glucose (BG). These patients must also be careful not to inject too much insulin because this could induce hypoglycemia (low BG), which can be fatal. Patients...