Browsing by Subject "Artificial Intelligence"
Now showing items 1-17 of 17
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A Dilemma for Criminal Justice Under Social Injustice
(2019)A moral dilemma confronts criminal justice in unjust states. If the state punishes marginalized citizens whose crimes are connected to conditions of systemic injustice the state has failed to alleviate, it perpetuates a ... -
Accelerated Multi-Criterial Optimization in Radiation Therapy using Voxel-Wise Dose Prediction
(2020)In external beam radiation therapy (EBRT) for cancer patients, it is highly desirable to completely eradicate the cancerous cells for the purpose of improving the patient’s quality of life and increasing the patient’s likelihood ... -
An active learning approach for rapid characterization of endothelial cells in human tumors.
(PLoS One, 2014)Currently, no available pathological or molecular measures of tumor angiogenesis predict response to antiangiogenic therapies used in clinical practice. Recognizing that tumor endothelial cells (EC) and EC activation and ... -
Application of Stochastic Processes in Nonparametric Bayes
(2014)This thesis presents theoretical studies of some stochastic processes and their appli- cations in the Bayesian nonparametric methods. The stochastic processes discussed in the thesis are mainly the ones with independent ... -
Artificial Intelligence for added value in the creation, implementation, and evaluation of national export strategies
(2022-04-22)A National Export Strategy (NES) is an action plan that sets priorities, allocates resources, and specifies actions to strengthen an economy’s international trade capabilities, seeking to enhance its economic growth and ... -
Artificial Intelligence Powered Direct Prediction of Linear Accelerator Machine Parameters: Towards a New Paradigm for Patient Specific Pre-Treatment QA
(2021)Purpose: Traditional pre-treatment patient specific QA is known for its high workload for physicist, ineffectiveness at identifying clinically relevant dosimetric uncertainties of treatment plans, and incompatibility with ... -
Automatic annotation of spatial expression patterns via sparse Bayesian factor models.
(PLoS Comput Biol, 2011-07)Advances in reporters for gene expression have made it possible to document and quantify expression patterns in 2D-4D. In contrast to microarrays, which provide data for many genes but averaged and/or at low resolution, ... -
Development of a neuro-fuzzy technique for automated parameter optimization of inverse treatment planning.
(Radiation oncology (London, England), 2009-01)BACKGROUND: Parameter optimization in the process of inverse treatment planning for intensity modulated radiation therapy (IMRT) is mainly conducted by human planners in order to create a plan with the desired dose distribution. ... -
Essays on Technological Change: Firm Organization, Problem Selection, and Diffusion
(2020)This dissertation investigates three aspects of technological change. In the first essay, I build on prior research that suggests new ventures are often more innovative than established firms. One unexplored reason for this ... -
Feature Selection for Value Function Approximation
(2011)The field of reinforcement learning concerns the question of automated action selection given past experiences. As an agent moves through the state space, it must recognize which state choices are best in terms of allowing ... -
Gene selection using iterative feature elimination random forests for survival outcomes.
(IEEE/ACM Trans Comput Biol Bioinform, 2012-09)Although many feature selection methods for classification have been developed, there is a need to identify genes in high-dimensional data with censored survival outcomes. Traditional methods for gene selection in classification ... -
Genetic signatures in the envelope glycoproteins of HIV-1 that associate with broadly neutralizing antibodies.
(PLoS Comput Biol, 2010-10-07)A steady increase in knowledge of the molecular and antigenic structure of the gp120 and gp41 HIV-1 envelope glycoproteins (Env) is yielding important new insights for vaccine design, but it has been difficult to translate ... -
Highly Efficient Neuromorphic Computing Systems With Emerging Nonvolatile Memories
(2020)Emerging nonvolatile memory based hardware neuromorphic computing systems have enabled the implementation of general vector-matrix multiplication in a manner to fuse computation and memory at the same physical location. ... -
Information-driven Sensor Path Planning and the Treasure Hunt Problem
(2008-04-25)This dissertation presents a basic information-driven sensor management problem, referred to as treasure hunt, that is relevant to mobile-sensor applications such as mine hunting, monitoring, and surveillance. The objective ... -
Knowledge-based IMRT treatment planning for prostate cancer.
(2011)The goal of intensity-modulated radiation therapy (IMRT) treatment plan optimization is to produce a cumulative dose distribution that satisfies both the dose prescription and the normal tissue dose constraints. The typical ... -
Optimized approach to decision fusion of heterogeneous data for breast cancer diagnosis.
(Med Phys, 2006-08)As more diagnostic testing options become available to physicians, it becomes more difficult to combine various types of medical information together in order to optimize the overall diagnosis. To improve diagnostic performance, ... -
Theological Librarian vs. Machine: Taking on the Amazon Alexa Show (with Some Reflections on the Future of the Profession)
(Theological Librarianship, 2017-10)
