Daniel Addison, MSHI

Chicago, Illinois, United States Contact Info
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About

Accomplished Information Security Technology CEO with a proven track record of leading…

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Contributions

Activity

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Experience & Education

  • Health Blockchain Security Services (HCISS) LLC

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Licenses & Certifications

Publications

Courses

  • Health Care Data

    BHIS437

  • Health Information Systems Analysis & Design

    BHIS520

  • Informatics for the Clinical Investigator

    BHIS509

  • Management of HC Data Communication Systems

    BHIS515

  • Transforming Healthcare using Business Intelligence and Predictive Analytics

    BHIS529

Projects

  • Breast Cancer Detection - ML

    This project consist of detecting breast cancer using machine learning model algorithms such as support vector machine (SVM) and K-Nearest Neighbor (KNN).

    See project

  • Heart Disease Prediction

    Project consist of using Neural Networks to predict heart diseases based on attributes such as blood pressure and etc.

    See project

  • SUM-IT Health Analytics - Patient Engagement and Activation

    Obtained and analyze data from multiple data sources; collaborated on the analysis and design of visualizations with Mila Smith using Tableau for a white paper titled, "Patient Engagement and Activation: the last mile towards healthier outcomes," by Miriam Isola and Kathy Schneider (http://www.sumithealthanalytics.com/news/)

    Other creators
    See project

  • Blockchain Cryptocurrency Dancoin

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    Developed a Cryptocurrency Bitcoin called Dancoin utilizing the Blockchain decentralize platform Ehethereum Solidity.

    See project

  • Autistic Spectrum Disorder Screening using Machine Learning

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    This particular project is focusing on performing childhood autistic spectrum Disorder (ASD) screening based on individual characteristics and behavioral patterns using supervised learning. Also, we will build and deploy a neural network using the Keras API.

    See project

  • Board Game Review (Supervised Learning)

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    This project is to aid gaming companies in search for measures to ensure that their product receive good reviews. It uses ML supervised learning methods linear regression model and nonlinear random forest regression model to predict the average review a board game received based on characteristics such as minimum and maximum number of players, playing time, complexity, etc.

    See project

  • Medical Treatment Project

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    This project is about solving the problem of interpreting genetic mutations being done manually. I am developing a machine learning algorithm that automatically classifies genetic variations for medical treatment.

    See project

  • Security as a Service (SecaaS) for a Rehabilitation Center Project

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    Other creators
    • Joanna Cloutier Lisa Magundayao and Debora Waldron

Honors & Awards

  • Masters of Science Degree

    UIC

  • Bachelors of Science Degree

    -

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