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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?
$begingroup$
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?
machine-learning neural-network deep-learning data-mining data-science-model
$endgroup$
add a comment |
$begingroup$
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?
machine-learning neural-network deep-learning data-mining data-science-model
$endgroup$
add a comment |
$begingroup$
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?
machine-learning neural-network deep-learning data-mining data-science-model
$endgroup$
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
machine-learning neural-network deep-learning data-mining data-science-model
asked Mar 19 at 6:22
LijoLijo
1113
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add a comment |
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