Global Health Statistics Dataset

Key Features of the Dataset:

• Disease prevalence, incidence, and mortality rates
• Effectiveness of medical treatments
• Healthcare infrastructure metrics across different regions
• Data from multiple countries and spanning several years

Dataset Use Cases

This dataset can be applied in various fields, including:

• Healthcare Policy Analysis: Analyze the global distribution of diseases and identify regions needing more healthcare investment or intervention.
• Epidemiological Studies: Explore correlations between disease patterns and socio-economic factors like income, education, and urbanization to improve health outcomes.
• Machine Learning and Predictive Modeling: Train AI models to predict disease trends, mortality rates, and the effectiveness of treatments based on historical and real-time data.
• Global Health Research and Public Health Campaigns: Identify at-risk populations and regions requiring focused public health initiatives and interventions.

Applications in Research and Machine Learning:

• Predictive analysis for disease outbreaks and healthcare system strain
• Data-driven decision-making for healthcare funding and resource allocation
• Evidence-based policy formulation for global health improvements

This dataset is sourced from Kaggle.