This project is about statistically analyzing risk factors for heart disease and performing A/B testing, descriptive and inferential statistics to provide health care plans and strategies to better understand the risk factors assocaited with heart disease and give key insights into what factors contribute most heavily and least heavily to the de…

Healthcare Analytics and Machine Learning: Dementia Prediction and Data Insights demonstrating data analysis, predictive modeling, and visualization techniques applied to healthcare data

Apply Data Analytics Techniques on Autism dataset to discover hidden patterns that would be leveraged in decision making.

Discover a curated collection of dynamic Power BI dashboards covering financial analytics, HR metrics, streaming service trends, real estate dynamics, and more. Meticulously designed for comprehensive data exploration, this repository continues to expand with new and impactful visualizations.

A comprehensive Power BI project analysing healthcare industry data, exploring patient demographics, hospital performance, and payer-provider dynamics through interactive visualizations & made executive summary report that provide actionable insights for strategic decision-making.

Demonstrating the implementation and value of the Bayesian statistics framework in healthcare

Identification of high-risk patients unsuitable for medical procedure. Cleaned claims of inconsistent quality and built meta prediction model. Fairness adjusted AUC score ranked top 20% of more than 200 participating teams.

In this repository, explore insightful solutions through exploratory data analysis focusing on mental health problems. Gain valuable insights into understanding and addressing key challenges in this critical domain.

Model to detect if individual has Parkinson's disease using Python Pandas, Numpy, xgbclassifier, MinMaxScaler, classification_report, train_test_split, and seaborn

Group project for the course BUDT704: Data Processing and Analysis using Python

Conduct comprehensive healthcare data analysis to derive insights, improve patient outcomes, and optimize operational efficiency through advanced statistical methodologies and machine learning techniques. Delivering actionable intelligence for informed decision-making.

Brain Tumor Detection using Deep Learning on AWS SageMaker: A project focused on building and training a deep learning model to detect brain tumors in MRI images. Leveraging AWS SageMaker and Ground Truth, we explore binary classification techniques for accurate diagnosis.

this Is my HealthCare Website under Hack-a-thon HackFest( Delhi/NCR) GEEKS FOR Geeks which is still in working .The system should continuously gather and analyze healthcare data while promoting healthy lifestyles and wellness practices.

A binary classification using Convolution Neural Network (CNN, or ConvNet) model.

Epidemiology course materials on the basic principles from my Undergraduate Degree

This repository contains the code components of work carried out for analyzing the Medical Provider Fraud Detection dataset with the intent to find most important features to crack down the potentially fraud providers.

Heart Disease Analysis to explore, diagnose and highlight potential factors to predict the disease chance in future.