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SrijanShovit / HealthLearning

A repo comprising of various Machine Learning and Deep Learning projects in healthcare domain.
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Liver Disease Prediction | Dataset Exploration and EDA #78

Closed W-ight closed 5 months ago

W-ight commented 6 months ago

Is your feature request related to a problem? Please describe. An model which predict whether a patient is a liver patient or not, based on various parameters is also an issue for Health Learning

Describe the solution you'd like I want to add a ML Liver Disease prediction model which can classify if a person is liver patient or not up to an accuracy.

@SrijanShovit I would like to work on this. Please assign it to me under gssoc24

SrijanShovit commented 6 months ago

Which dataset? @W-ight

W-ight commented 6 months ago

There is a dataset name Indian Liver Patient Records in Kaggle I can use that. Or if you have any other idea for dataset i am open to that also @SirjanShovit

SrijanShovit commented 6 months ago

Ok proceed with Dataset exploration and EDA. For reference, you can find other #1. and #2. Issues

W-ight commented 6 months ago

Thanks. I will start working on it

github-actions[bot] commented 6 months ago

This issue has been automatically closed because it has been inactive for more than 7 days. If you believe this is still relevant, feel free to reopen it or create a new one. Thank you!

SrijanShovit commented 5 months ago

Re opening or any one to take it up

Sayeda-fatima commented 5 months ago

@SrijanShovit I would like to work on this issue. Please assign it to me. I'm a GSSoC'24 contributor

Taranpreet10451 commented 5 months ago

Can you please assign this to me.

Sayantan-Karmakar commented 5 months ago

I would like to complete the prediction model using Indian liver patient records from kaggle. Link : https://www.kaggle.com/datasets/uciml/indian-liver-patient-records Kindly assign me this.

github-actions[bot] commented 5 months ago

This issue has been automatically closed because it has been inactive for more than 7 days. If you believe this is still relevant, feel free to reopen it or create a new one. Thank you!