The use of predictive models in dynamic treatment planning
| Autor: | Kristin Siggeirsdottir, John R. Woodward, Vilmundur Gudnason, Ragnheidur D. Brynjolfsdottir, Saemundur O. Haraldsson |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
business.industry
Computer science 02 engineering and technology Machine learning computer.software_genre 03 medical and health sciences 0302 clinical medicine Health care 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing 030212 general & internal medicine Artificial intelligence Vocational rehabilitation Data mining business Radiation treatment planning computer Predictive modelling |
| Zdroj: | ISCC |
| DOI: | 10.1109/iscc.2017.8024536 |
| Popis: | With the expanding load on healthcare and consequent strain on budget, the demand for tools to increase efficiency in treatments is rising. The use of prediction models throughout the treatment to identify risk factors might be a solution. In this paper we present a novel implementation of a prediction tool and the first use of a dynamic predictor in vocational rehabilitation practice. The tool is periodically updated and improved with Genetic Improvement of software. The predictor has been in use for 10 months and is evaluated on predictions made during that time by comparing them with actual treatment outcome. The results show that the predictions have been consistently accurate throughout the patients' treatment. After approximately 3 week learning phase, the predictor classified patients with 100% accuracy and precision on previously unseen data. The predictor is currently being successfully used in a complex live system where specialists have used it to make informed decisions. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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