💡[Feature]: Drug Classification System using Supervised learning #1375
Description
Is there an existing issue for this?
- I have searched the existing issues
Feature Description
Using various different supervised machine Learning algorithm , i want to make a drug classification application using Streamlit and analysis on notebook using below Kaggle drug classification Dataset :
https://www.kaggle.com/datasets/lykin22/drug-data
the input features will be :
ge
Age of the Patient
Sex
Gender of the patients
BP
Blood Pressure Levels
Cholesterol
Cholesterol Levels
Na_to_K
Sodium to potassium Ration in Blood
output :
Drug
(among five possible types such as DrugA, DrugB , DrugC , DrugY , DrugX)
Dear Sanjay KV, i am, a gssoc-2024 extended contributor. i want to work ion this PR for gssochacktoberfest 2024. please asisgn this issue to me along with label hacktoberfest-acceptedtag and gssoc'24-extended tag.
Use Case
Physicians can use the model to predict the most appropriate drug type for a patient based on their age, sex, blood pressure levels, cholesterol levels, and sodium-to-potassium ratio. This allows for tailored treatment plans, improving efficacy and reducing adverse reactions.
Benefits
Personalized Medicine
Benefit: The model enables tailored drug prescriptions by analyzing individual patient characteristics like age, sex, blood pressure, cholesterol, and electrolyte balance. This leads to better treatment outcomes, as drugs can be matched to the specific needs of each patient.
2. Improved Accuracy in Drug Selection
Benefit: The model minimizes human error by systematically considering multiple health factors to predict the most suitable drug. This reduces the likelihood of incorrect prescriptions and enhances overall treatment accuracy.
3. Reduced Side Effects
Benefit: By considering key health indicators (e.g., sodium-to-potassium ratio, blood pressure), the model helps in selecting drugs that are less likely to cause adverse side effects, improving patient safety and reducing complications.
Add ScreenShots
NA
Priority
High
Record
- I have read the Contributing Guidelines
- I'm a GSSOC'24 contributor
- I want to work on this issue