类别 全部 - interventions - challenges - outcomes - ai

作者:Jeremy Brommersma 7 天以前

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Toward Population Health Intelligence: When Artificial Intelligence Meets Population Health Research

Artificial intelligence is transforming the field of disease prediction and health interventions, offering a significant improvement over traditional methods. By leveraging various types of AI models, predictions can be frequently updated, leading to cost-effective profiling and the ability to manage incomplete data efficiently.

Toward Population Health Intelligence: When Artificial Intelligence Meets Population Health Research

AI's Role in Optimizing Health Interventions and Real World Results

Real World Results

Cost reduction
Better results with less data
Testing the model

Using AI for Health Interventions

Urban planning
Reducing health inequalities
Targeted interventions

Ai's predictive power in Finding Disease

Case Study: CPHP AI Model

Dealing with missing data
Cost-effective profiling
CPHP overview

How Ai helps predict Disease

Types of AI models
AI updates predictions
Old prediction methods

Toward Population Health Intelligence: When Artificial Intelligence Meets Population Health Research

Challenges and Considerations for AI in Public Health

AI and Better Health Predictions
Improving health outcomes
Multimodal learning
Combining data types:
Challenges and Opportunities
Room for improvement
Making AI understandable
Uncertainty in predictions