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@data-intelligence-for-health-lab

Data Intelligence for Health Lab

We are a group of health data science researchers in the Cumming School of Medicine, University of Calgary.

Popular repositories

  1. Lpheada-Labelled-Public-HEAlth-DAtaset Lpheada-Labelled-Public-HEAlth-DAtaset Public

    LPHEADA is a multicountry and fully Labelled digital Public HEAlth DAtaset of tweets originated in Australia, Canada, UK, or US between November 28th, 2018 to June 19th, 2020. This dataset contains…

    Jupyter Notebook 7 1

  2. ICD10-Unsupervised-Feature-Selection ICD10-Unsupervised-Feature-Selection Public

    Unsupervised Feature Selection to Identify Important ICD-10 Codes for Machine Learning

    Python 4 1

  3. BloodLaboratoryTestRedundancy BloodLaboratoryTestRedundancy Public

    Python 3

  4. Discharge-Prediction_eICU-CRD Discharge-Prediction_eICU-CRD Public

    This repository presents the implementation of different machine learning architectures to determine the efficacy of the Acute Physiology andChronic Health Evaluation (APACHE) IV score as well as t…

    Jupyter Notebook 2 2

  5. mHealth_Emotional_State-Transition_Detection_Public mHealth_Emotional_State-Transition_Detection_Public Public

    Jupyter Notebook 2 1

  6. NLP--modes_of_communication--families-healthcare_professionals NLP--modes_of_communication--families-healthcare_professionals Public

    Natural language processing to measure communication between healthcare professionals and family members of critically ill patients

    Python

Repositories

Showing 10 of 13 repositories
  • ai4ph-data-challenge-2024 Public

    This is the main site for the 2024 AI4PH Summer Institute Data Challenge.

    data-intelligence-for-health-lab/ai4ph-data-challenge-2024’s past year of commit activity
    0 0 0 0 Updated Jun 17, 2024
  • Evaluation_metrics_considering_case_difficulty Public
    data-intelligence-for-health-lab/Evaluation_metrics_considering_case_difficulty’s past year of commit activity
    Jupyter Notebook 0 0 0 0 Updated Mar 8, 2024
  • Measuring_Case_Difficulty Public
    data-intelligence-for-health-lab/Measuring_Case_Difficulty’s past year of commit activity
    Jupyter Notebook 0 0 0 0 Updated Nov 9, 2023
  • ICD10-Unsupervised-Feature-Selection Public

    Unsupervised Feature Selection to Identify Important ICD-10 Codes for Machine Learning

    data-intelligence-for-health-lab/ICD10-Unsupervised-Feature-Selection’s past year of commit activity
    Python 4 MIT 1 0 0 Updated Sep 16, 2023
  • ICU_outcome_prediction_Transfer_Learning Public Forked from maruthi-mk/ICU_outcome_prediction_Transfer_Learning

    Using domain adaptation and inductive transfer learning to improve patient outcome prediction in the intensive care unit

    data-intelligence-for-health-lab/ICU_outcome_prediction_Transfer_Learning’s past year of commit activity
    Python 0 MIT 1 0 0 Updated Jun 13, 2023
  • delirium_prediction Public
    data-intelligence-for-health-lab/delirium_prediction’s past year of commit activity
    Python 0 MIT 1 0 0 Updated Jun 8, 2022
  • BloodLaboratoryTestRedundancy Public
    data-intelligence-for-health-lab/BloodLaboratoryTestRedundancy’s past year of commit activity
    Python 3 0 0 0 Updated Mar 24, 2022
  • python-starter Public

    A simple starter project written in python!

    data-intelligence-for-health-lab/python-starter’s past year of commit activity
    0 0 0 0 Updated Mar 3, 2022
  • Lpheada-Labelled-Public-HEAlth-DAtaset Public

    LPHEADA is a multicountry and fully Labelled digital Public HEAlth DAtaset of tweets originated in Australia, Canada, UK, or US between November 28th, 2018 to June 19th, 2020. This dataset contains 366,405 crowd-generated labels (three labels per tweet) for 122,135 PASS-related tweets, labelled by 708 unique annotators on Amazon Mechanical Turk.

    data-intelligence-for-health-lab/Lpheada-Labelled-Public-HEAlth-DAtaset’s past year of commit activity
    Jupyter Notebook 7 MIT 1 0 0 Updated Feb 21, 2022
  • CrowdSourcing-for-Digital-Public-Health-Surveillance Public

    To explore and evaluate the application of crowdsourcing, in general, and AMT, in specific, for developing digital public health surveillance systems, we collected 296,166 crowd-generated labels for 98,722 tweets, labelled by 610 AMT workers, to develop machine learning (ML) models for detecting behaviours related to physical activity, sedentary…

    data-intelligence-for-health-lab/CrowdSourcing-for-Digital-Public-Health-Surveillance’s past year of commit activity
    Jupyter Notebook 0 MIT 0 0 0 Updated Feb 14, 2022
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