17643197. PREDICTING AND EXPLAINING THE EFFECTIVENESS OF SOCIAL PROGRAMS simplified abstract (INTERNATIONAL BUSINESS MACHINES CORPORATION)
PREDICTING AND EXPLAINING THE EFFECTIVENESS OF SOCIAL PROGRAMS
Organization Name
INTERNATIONAL BUSINESS MACHINES CORPORATION
Inventor(s)
Natalia Mulligan of Dublin (IE)
Marco Luca Sbodio of Castaheany (IE)
Joao H. Bettencourt-silva of Dublin (IE)
Vanessa Lopez Garcia of Dublin (IE)
Conor Patrick Cullen of Clontarf (IE)
PREDICTING AND EXPLAINING THE EFFECTIVENESS OF SOCIAL PROGRAMS - A simplified explanation of the abstract
This abstract first appeared for US patent application 17643197 titled 'PREDICTING AND EXPLAINING THE EFFECTIVENESS OF SOCIAL PROGRAMS
Simplified Explanation
The patent application describes a method for predicting the effectiveness of a social program for a specific patient at different points in time. It also provides a score indicating the accuracy of the prediction and an explanation of the prediction.
- The processor receives a request from a user.
- If the social program database contains historical data on the given social program, the processor analyzes a set of patients associated with the program.
- Using a prediction model trained to predict effectiveness and confidence scores, the processor predicts the effectiveness of the social program for the given patient at the specified points in time.
- The prediction of the effectiveness of the social program for the given patient is then outputted to the user.
Potential Applications
- Healthcare: Predicting the effectiveness of social programs for patients to optimize treatment plans.
- Social Services: Assessing the potential impact of social programs on individuals to allocate resources efficiently.
- Research: Analyzing historical data to understand the effectiveness of different social programs and improve future interventions.
Problems Solved
- Lack of personalized prediction: This technology allows for individualized predictions of the effectiveness of social programs for specific patients.
- Resource allocation: By predicting the effectiveness of social programs, resources can be allocated more effectively to those who will benefit the most.
- Treatment optimization: The prediction scores and explanations help in optimizing treatment plans by identifying the most effective social programs for each patient.
Benefits
- Personalized approach: Patients can receive tailored social programs based on the predicted effectiveness for their specific needs.
- Efficient resource allocation: By accurately predicting effectiveness, resources can be allocated to those who are likely to benefit the most, maximizing the impact of social programs.
- Improved treatment outcomes: Optimizing treatment plans based on predicted effectiveness can lead to better patient outcomes and overall program success.
Original Abstract Submitted
In an approach for predicting an effectiveness of a given social program for a given patient at one or more points in time and for providing a score indicating the accuracy of the prediction and an explanation of the prediction, a processor receives a request from a user. Responsive to determining a social program database contains historical data on the given social program, a processor analyzes a set of patients associated with the given social program. A processor predicts the effectiveness of the given social program for the given patient at the one or more points in time using a prediction model trained to predict an effectiveness score and a confidence score. A processor outputs a prediction of the effectiveness of the given social program for the given patient at the one or more points in time to the user.
