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Predictive Analytics and Decision Support for Heart Failure patients
In the last few years, legislations such as the Patient Protection and A ordable Care Act, also known as Obamacare, have emphasised the need for improving the quality of health care. Part of the programs introduced by this Act is the Hospital Readmissions Reduction Program (HRRP) which reduces payments to hospitals with excess ...
Prediction and Privacy in Healthcare Analytics
In the past decade, the United States federal government has made improving the healthcare system a major focus with legislation such as the Patient Protection and Affordable Care Act and the financial incentives for meaningful use within the American Recovery and Reinvestment Act. This focus has caused an increase in data ...
Inferring Big 5 Personality from Online Social Networks
Online social networks are very popular with millions of people creating online profiles and sharing personal information including their interests, activities, likes/dislikes and thoughts with their friends and family. This rich user generated content from social media makes them an ideal platform to study human behavior. ...
Intervention Recommendations to Minimize the 30-Day Risk-of-Readmission for Heart Failure
In this thesis, we investigate the problem of designing personalized intervention strategies to minimize 30-day readmission risk for heart failure (HF) patients. In particular, we propose a novel framework that recommends personalized intervention to the patients by analyzing the complex interplay among a multitude of factors, ...
Predicting Risk of Re-hospitalization for Congestive Heart Failure Patients
(2013-04-17)
Congestive Heart Failure (CHF) is one of the leading causes of hospitalization, and studies show that many of these admissions are readmissions. Identifying patients who are at a greater risk of hospitalization, can guide implementation of appropriate plans to prevent these readmissions. In the field of medical sciences, ...
Selecting Robust Strategies in RTS Games via Concurrent Plan Augmentation
The multifaceted complexity of real-time strategy (RTS) games requires AI systems to break down policy computation into smaller subproblems such as strategic planning, tactical planning, and reactive control. To further simplify planning at the strategic and tactical levels, state-of-the-art automatic techniques such as ...
Distributed Diverging Topic Models: A Novel Algorithm for Large Scale Topic Modeling in Spark
In their 2001 work Latent Dirichlet Allocation, Blei, Ng, and Jordan proposed the generative model of the same name that has since become the basis for most research in the field of topic modeling. The model overcame many of the shortcomings of previous probabilistic models such as allowing the inference of topics in documents ...
Energy-aware Workflow Scheduling and Fuzzy Logic Based Capacity Provisioning in Cloud Environment
The increasing need of large-scale data centers has brought new challenges to the development of energy-efficiency techniques. Although many optimization techniques have been proposed, most of them neglect the characteristics of tasks and fail to consider the dependencies between tasks. Therefore, more comprehensive optimization ...
Discrete Gaussian Sampling for Low-Power Devices
Sampling from the discrete Gaussian probability distribution is used in lattice-based cryptosystems. A need for faster and memory-efficient samplers has become a necessity for improving the performance of such cryptosystems. We propose a new algorithm for sampling from the Gaussian distribution that can efficiently change ...
Gene Network Inference using Machine Learning and Graph Algorithms on Big Biomedical Data
Gene networks capture the interactions between different biological entities. These gene networks have many applications in modern day biology. In particular, gene networks can help to shed light on the underlying mechanisms of diseases. Advances in biotechnology have led to the generation of different types of genome-wide ...