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A novel knowledge based conformation sampling algorithm and applications in drug discovery
(2016-08-12)
Computational approaches have become important tools in drug discovery. Computational technologies have been developed for application in all aspects of the drug discovery process including target identification, lead ...
Evaluation of a novel terminology to categorize clinical document section headers and a related clinical note section tagger
(2007-08-03)
The aims of this project are to 1) build and evaluate a terminology that provides categorization labels, or tags, for common segments within clinical documents, and 2) to evaluate a tool to parse and label natural-language ...
Computational Phenotyping and Phenome-wide Association Studies: Leveraging Machine Learning and Natural Language Processing to Understand Electronic Health Record Data
(2015-08-27)
The aims of this project are 1) to evaluate various data sources and algorithms for identifying hypertensive individuals within the electronic health record, and 2) to develop and evaluate a novel method for identifying ...
Scalable Natural Language De-identification based on Machine Learning Approaches
(2018-03-27)
Electronic medical record (EMR) systems have been progressively adopted in numerous aspects of clinical care and healthcare endeavors. As the quantity and diversity of such data grows, so too has its repurposing to support ...
Structure prediction and variant interpretation of membrane proteins aided by machine learning algorithms
(2018-03-24)
Helical membrane proteins (HMPs) play essential roles in various biological processes. Despite their prevalence in the genome, a very small portion (~2%) of structures in the Protein Data Bank are HMPs, partially due to ...
A Machine Learning Approach to Modeling Dynamic Decision-Making in Strategic Interactions and Prediction Markets
(2017-03-28)
My overarching modeling goal for my dissertation is to maximize generalization – some function of data and knowledge – from one sample, with its observations drawn independently from the distribution D, to another sample ...
Learning the State of Patient Care and Opportunities for Improvement from Electronic Health Record Data with Applications in Breast Cancer Patients
(2017-04-17)
Patient care is complex and imperfect. Understanding and improving patient care requires clinical datasets and scientific methodology. We designed a set of methods to characterize the state of patient care and identify ...
A Data-Driven Analysis of Environmental Migration in Coastal Bangladesh
(2019-07-17)
The decision to migrate is complex and is often influenced by a combination of economic, social, political, and environmental pressures. Seasonal, internal migration is a common strategy for livelihood diversification in ...
Using Statistical Learning Methods for Better Spectrum Classification
(2014-07-16)
Shotgun proteomics has become a widely used technology for identifying a large number of peptides and proteins in complex biological samples. However, any single score function from most search algorithms to evaluate the ...
Using Machine Learning to Identify and Predict Gentrification in Nashville, Tennessee.
(2019-07-24)
Gentrification is a polarizing and elusive type of neighborhood change that disproportionately threatens our community’s most vulnerable populations. The lived consequences of gentrification have merited a substantial ...