💡[Feature]: HIV disease prediction using Machine learning

[RajKhanke]

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Feature Description

Kaggle dataset : https://www.kaggle.com/datasets/ishigamisenku10/hiv-prediction

(The following dataset gives information about the person suffering from HIV. This dataset is taken from a hospital. Most of the people gave similar information about their past experiences. Based on those experiences, features have been created.)

The project aims to classify whether the person has the likeliness to suffer from HIV (human immuno-deficiency virus) or not based on various input features in the data using ML models

as a solution i will do a complete data analysis ,EDA , feature engineering and take input on Streamlit application to produce the output.

Use Case

Early Diagnosis: Machine learning algorithms can analyze medical data to detect early signs of HIV, enabling prompt treatment and better management of the disease.
Resource Allocation: Predictive models can help health organizations identify high-risk populations, optimizing resource distribution and targeted interventions.

Benefits

Improved Accuracy: Machine learning enhances diagnostic accuracy by identifying subtle patterns in complex datasets that may be overlooked by traditional methods.
Personalized Treatment: By predicting individual responses to different treatment options, machine learning facilitates personalized healthcare, improving patient outcomes and quality of life.

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[RajKhanke]

@Avdhesh-Varshney @TAHIR0110 please assign this issue to me along with gssoc'24 level and label