{
  "id": 538333,
  "title": "Paper sharing",
  "url": "/competitions/brist1d/discussion/538333",
  "author_name": "",
  "post_date": "2024-10-08T12:25:27.248280200Z",
  "votes": 22,
  "comment_count": 1,
  "views": 0,
  "content": "<p>1.Fill in missing value using VAE : <a href=\"https://arxiv.org/pdf/2410.00015\" target=\"_blank\">https://arxiv.org/pdf/2410.00015</a></p>\n<p>2.Integrating Bayesian Approaches and ExpertKnowledge for Forecasting Continuous GlucoseMonitoring Values in Type 2 Diabetes Mellitus: <a href=\"https://arxiv.org/pdf/2409.07315\" target=\"_blank\">https://arxiv.org/pdf/2409.07315</a></p>\n<p>3.From Glucose Patterns to Health Outcomes: A Generalizable FoundationModel for Continuous Glucose Monitor Data Analysis:<a href=\"https://arxiv.org/pdf/2408.11876\" target=\"_blank\">https://arxiv.org/pdf/2408.11876</a></p>\n<p>4.GARNN: An Interpretable Graph Attentive Recurrent Neural Network for Predicting BloodGlucose Levels via Multivariate Time Series <br>\n <a href=\"https://arxiv.org/pdf/2402.16230\" target=\"_blank\">https://arxiv.org/pdf/2402.16230</a></p>\n<p>more paper <a href=\"https://arxiv.org/search/?query=Blood+Glucose&amp;searchtype=all&amp;source=header\" target=\"_blank\">https://arxiv.org/search/?query=Blood+Glucose&amp;searchtype=all&amp;source=header</a></p>",
  "messages": [
    {
      "id": "3009843",
      "postDate": "10/08/2024 12:25:27",
      "content": "<p>1.Fill in missing value using VAE : <a href=\"https://arxiv.org/pdf/2410.00015\" target=\"_blank\">https://arxiv.org/pdf/2410.00015</a></p>\n<p>2.Integrating Bayesian Approaches and ExpertKnowledge for Forecasting Continuous GlucoseMonitoring Values in Type 2 Diabetes Mellitus: <a href=\"https://arxiv.org/pdf/2409.07315\" target=\"_blank\">https://arxiv.org/pdf/2409.07315</a></p>\n<p>3.From Glucose Patterns to Health Outcomes: A Generalizable FoundationModel for Continuous Glucose Monitor Data Analysis:<a href=\"https://arxiv.org/pdf/2408.11876\" target=\"_blank\">https://arxiv.org/pdf/2408.11876</a></p>\n<p>4.GARNN: An Interpretable Graph Attentive Recurrent Neural Network for Predicting BloodGlucose Levels via Multivariate Time Series <br>\n <a href=\"https://arxiv.org/pdf/2402.16230\" target=\"_blank\">https://arxiv.org/pdf/2402.16230</a></p>\n<p>more paper <a href=\"https://arxiv.org/search/?query=Blood+Glucose&amp;searchtype=all&amp;source=header\" target=\"_blank\">https://arxiv.org/search/?query=Blood+Glucose&amp;searchtype=all&amp;source=header</a></p>",
      "rawMarkdown": "1.Fill in missing value using VAE : https://arxiv.org/pdf/2410.00015\n\n2.Integrating Bayesian Approaches and ExpertKnowledge for Forecasting Continuous GlucoseMonitoring Values in Type 2 Diabetes Mellitus: https://arxiv.org/pdf/2409.07315\n\n3.From Glucose Patterns to Health Outcomes: A Generalizable FoundationModel for Continuous Glucose Monitor Data Analysis:https://arxiv.org/pdf/2408.11876\n\n4.GARNN: An Interpretable Graph Attentive Recurrent Neural Network for Predicting BloodGlucose Levels via Multivariate Time Series \n https://arxiv.org/pdf/2402.16230\n\nmore paper https://arxiv.org/search/?query=Blood+Glucose&searchtype=all&source=header",
      "votes": null
    },
    {
      "id": "3017191",
      "postDate": "10/14/2024 16:12:43",
      "content": "<p>Thanks for the papers. This has been an interesting project. My first on Kaggle, so I appreciate the information.</p>",
      "rawMarkdown": "Thanks for the papers. This has been an interesting project. My first on Kaggle, so I appreciate the information.",
      "votes": null
    }
  ],
  "comments": [
    {
      "id": 3017191,
      "author_name": "wibberding",
      "author_url": "",
      "post_date": "10/14/2024 16:12:43",
      "content": "<p>Thanks for the papers. This has been an interesting project. My first on Kaggle, so I appreciate the information.</p>",
      "votes": null,
      "replies": []
    }
  ],
  "raw_markdown_by_id": {
    "3009843": "1.Fill in missing value using VAE : https://arxiv.org/pdf/2410.00015\n\n2.Integrating Bayesian Approaches and ExpertKnowledge for Forecasting Continuous GlucoseMonitoring Values in Type 2 Diabetes Mellitus: https://arxiv.org/pdf/2409.07315\n\n3.From Glucose Patterns to Health Outcomes: A Generalizable FoundationModel for Continuous Glucose Monitor Data Analysis:https://arxiv.org/pdf/2408.11876\n\n4.GARNN: An Interpretable Graph Attentive Recurrent Neural Network for Predicting BloodGlucose Levels via Multivariate Time Series \n https://arxiv.org/pdf/2402.16230\n\nmore paper https://arxiv.org/search/?query=Blood+Glucose&searchtype=all&source=header",
    "3017191": "Thanks for the papers. This has been an interesting project. My first on Kaggle, so I appreciate the information."
  },
  "source": "meta"
}