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Adaptive Prognostic Models: Learning by Continuous Monitoring

Adaptive Prognostic Models: Learning by Continuous Monitoring. Robert Percevic Forschungsstelle für Psychotherapie. 1. symptom severity. time. 1. b. a. symptom severity. time. 1. symptom severity. time. 1. symptom severity. time. 2. symptom severity. time. 3. symptom severity.

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Adaptive Prognostic Models: Learning by Continuous Monitoring

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  1. Adaptive Prognostic Models: Learning by Continuous Monitoring Robert Percevic Forschungsstelle für Psychotherapie

  2. 1 symptom severity time

  3. 1 b a symptom severity time

  4. 1 symptom severity time

  5. 1 symptom severity time

  6. 2 ... ... symptom severity ... time

  7. 3 symptom severity time

  8. 3 symptom severity time

  9. 3 symptom severity time

  10. 2+3 Provided Information: oooo xooo ooox xoox xxxx

  11. 2+3 Es

  12. 4 Et ~ 4 weeks symptom severity time

  13. intake assessment 1st intermediate assessment symptom severity time

  14. intake assessment 1st intermediate assessment 2nd intermediate assessment symptom severity time

  15. Each patient will reach „functional range“ given enough time • The time a patient needs depends on symptom severity and chance • The prediction of this time is not accurate enough to govern discharge, but helpful in timing reassessment

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