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Model and Type for Medication Impact


Predicting contract churn/cancellation: Great model results does not work in the real worldData Type required in WekaPredicting survival on Haberman's datasetDesign language or artifact for data science modelType of model for space-characters recovery?Two-class classification model with multi-type input dataThe effect of the image type and the image conversion on deep learning CNN modelFinding the equation for a multiple and nonlinear regression model?Does the choice of error function impact the model parametrs?What are Machine learning model characteristics?













0












$begingroup$


I have following 3 datasets from various patients:



  • Diagnosis Dataset: Patient_Key, Diagnosis Code,Diagnosis Date

  • Medication Dataset: Patient_Key, Medication Name, Dose, Fill Date

  • Lab Result Dataset:: Patient Key,Lab Test Name,Lab Result Value,Test Date

For, all patients who have hypertension diagnosis preexisting at least 3 years ago, I need to find which medication is helping to reduce Creatinine value (lab result for Creatinine test). Should this be a supervised learning or unsupervised learning? What will be useful models for this objective?










share|improve this question









$endgroup$
















    0












    $begingroup$


    I have following 3 datasets from various patients:



    • Diagnosis Dataset: Patient_Key, Diagnosis Code,Diagnosis Date

    • Medication Dataset: Patient_Key, Medication Name, Dose, Fill Date

    • Lab Result Dataset:: Patient Key,Lab Test Name,Lab Result Value,Test Date

    For, all patients who have hypertension diagnosis preexisting at least 3 years ago, I need to find which medication is helping to reduce Creatinine value (lab result for Creatinine test). Should this be a supervised learning or unsupervised learning? What will be useful models for this objective?










    share|improve this question









    $endgroup$














      0












      0








      0


      1



      $begingroup$


      I have following 3 datasets from various patients:



      • Diagnosis Dataset: Patient_Key, Diagnosis Code,Diagnosis Date

      • Medication Dataset: Patient_Key, Medication Name, Dose, Fill Date

      • Lab Result Dataset:: Patient Key,Lab Test Name,Lab Result Value,Test Date

      For, all patients who have hypertension diagnosis preexisting at least 3 years ago, I need to find which medication is helping to reduce Creatinine value (lab result for Creatinine test). Should this be a supervised learning or unsupervised learning? What will be useful models for this objective?










      share|improve this question









      $endgroup$




      I have following 3 datasets from various patients:



      • Diagnosis Dataset: Patient_Key, Diagnosis Code,Diagnosis Date

      • Medication Dataset: Patient_Key, Medication Name, Dose, Fill Date

      • Lab Result Dataset:: Patient Key,Lab Test Name,Lab Result Value,Test Date

      For, all patients who have hypertension diagnosis preexisting at least 3 years ago, I need to find which medication is helping to reduce Creatinine value (lab result for Creatinine test). Should this be a supervised learning or unsupervised learning? What will be useful models for this objective?







      machine-learning neural-network deep-learning data-mining data-science-model






      share|improve this question













      share|improve this question











      share|improve this question




      share|improve this question










      asked Mar 19 at 6:22









      LijoLijo

      1113




      1113




















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