Eastern Illinois University

Eastern Illinois University
Not a member yet
    96689 research outputs found

    Fall Social

    No full text
    Fall Socialhttps://thekeep.eiu.edu/ahs_fall2025/1007/thumbnail.jp

    Fall Social

    No full text
    Fall Socialhttps://thekeep.eiu.edu/ahs_fall2025/1005/thumbnail.jp

    Ice Cream Social

    No full text
    Ice Cream Socialhttps://thekeep.eiu.edu/ahs_fall2025/1015/thumbnail.jp

    Ice Cream Social

    No full text
    Ice Cream Socialhttps://thekeep.eiu.edu/ahs_fall2025/1009/thumbnail.jp

    Welcome Back Bingo

    No full text
    Welcome Back Bingohttps://thekeep.eiu.edu/ahs_fall2025/1030/thumbnail.jp

    Disease Diagnosis Using Natural Language Processing and Deep Learning

    No full text
    This research presents an automated disease diagnosis framework that leverages natural language processing and deep learning to predict diagnosis codes from unstructured electronic health record (EHR) clinical notes. Using the MIMIC-III critical care dataset, clinical narratives such as discharge summaries and physician notes are extracted, validated, and preprocessed to construct a labeled corpus aligned with ICD-9 diagnoses. The study implements a pipeline comprising text cleaning, feature extraction, and supervised learning, and compares traditional models such as Logistic Regression and Bi-LSTM with transformer-based architectures built on BERT. Models are trained and evaluated with categorical cross-entropy loss and standard multi-class metrics, including accuracy, F1-score, and ROC-AUC, while hyperparameters such as learning rate, optimizer configuration, and training epochs are systematically tuned. Experimental results show that BERT-based classifiers substantially outperform conventional baselines, achieving higher accuracy and F1-scores and demonstrating strong robustness in handling complex clinical terminology and context. These findings highlight the potential of transformer-based NLP models to enhance clinical decision support and large-scale phenotyping, while also underscoring limitations related to label noise, dataset-specific bias, truncated input length, and the need for more comprehensive interpretability and multi-label modeling in future work

    Reflections at the Close of My Freshman Year As Editor

    No full text

    Organizational Pitfalls of the Dual-Identity Leader

    No full text
    The dual-identity leader (D-IL) is an individual assigned to one job description yet is, in practice, fulfilling an additional position’s role. This secondary role is self-determined; has not been assigned yet is being allowed by those with governance and/or executive authority. Three case examples of the D-IL are presented and discussed as a problematic leadership configuration for an organization. The personal characteristics driving this approach are identified as a foundation for clarifying the organizational consequences of such an executive leader. Preventative and corrective tactics are discussed that eliminate or minimize the adverse impact of the D-IL’s organizational behavior

    Case Study: The Economic and Legal Challenges Moving from a Township to a City

    No full text
    The paper examines the economic and legal challenges moving from a township to a municipality in the state of Minnesota. One of the authors was a member of the township board as they went through the process of educating the citizens on the risks and rewards of changing from a township to a municipality

    ENG 1001G-015 College Composition I Critical Reading & Source Based Writing

    No full text

    52,557

    full texts

    96,689

    metadata records
    Updated in last 30 days.
    Eastern Illinois University
    Access Repository Dashboard
    Do you manage Open Research Online? Become a CORE Member to access insider analytics, issue reports and manage access to outputs from your repository in the CORE Repository Dashboard! 👇