About this Research Topic
Clinical prediction models (CPMs) use multiple predictors to estimate the absolute individual probability/risk that a certain outcome is present (diagnostic prediction model) or will occur in the future (prognostic prediction model). To date, CPMs are increasingly used to supplement clinical reasoning and decision making in modern medicine. CPMs are often used to help healthcare professionals make patient-oriented decisions about further treatment and to inform individuals about their risks of having (i.e. diagnosis) or developing (i.e. prognosis) a particular disease or outcome.
In dentistry, CPMs are not very widely developed and used in clinical practice to date, although some specific CPMs have been commonly used to predict an oral health outcome (e.g. Cariogram and CAMBRA for prediction of caries risk). Therefore, the main goals of this Research Topic are to raise the awareness of dental clinicians and dental researchers regarding the importance of CPMs and to promote the use of CPMs in the dental field. To achieve this goal, the Research Topic aims to encourage researchers and clinicians to develop, externally validate, and update CPMs for oral health outcomes using traditional or advanced approaches (e.g. machine learning) and to encourage researchers to evaluate the impact of the prediction models in dentistry on clinical decision making and patient outcomes.
We welcome researchers and clinicians to contribute to this Research Topic in the form of original research and systematic reviews on any aspects of CPMs in oral health outcomes. Possible topics include (but are not limited to):
1. Development of a prediction model for oral health outcomes;
2. External validation of an existing prediction model for oral health outcomes;
3. Updating/adjusting an existing prediction model for oral health outcomes;
4. The impact of a prediction model on clinical decision making and patient outcomes in dentistry;
5. A cost-benefit analysis to justify the use of clinical prediction models;
6. A systematic review on the performance of prediction models for oral health outcomes.
High quality manuscripts using both traditional approaches and more advanced approaches (e.g. machine learning) for the modeling/validation/updating are welcome.
In dentistry, CPMs are not very widely developed and used in clinical practice to date, although some specific CPMs have been commonly used to predict an oral health outcome (e.g. Cariogram and CAMBRA for prediction of caries risk). Therefore, the main goals of this Research Topic are to raise the awareness of dental clinicians and dental researchers regarding the importance of CPMs and to promote the use of CPMs in the dental field. To achieve this goal, the Research Topic aims to encourage researchers and clinicians to develop, externally validate, and update CPMs for oral health outcomes using traditional or advanced approaches (e.g. machine learning) and to encourage researchers to evaluate the impact of the prediction models in dentistry on clinical decision making and patient outcomes.
We welcome researchers and clinicians to contribute to this Research Topic in the form of original research and systematic reviews on any aspects of CPMs in oral health outcomes. Possible topics include (but are not limited to):
1. Development of a prediction model for oral health outcomes;
2. External validation of an existing prediction model for oral health outcomes;
3. Updating/adjusting an existing prediction model for oral health outcomes;
4. The impact of a prediction model on clinical decision making and patient outcomes in dentistry;
5. A cost-benefit analysis to justify the use of clinical prediction models;
6. A systematic review on the performance of prediction models for oral health outcomes.
High quality manuscripts using both traditional approaches and more advanced approaches (e.g. machine learning) for the modeling/validation/updating are welcome.
Keywords: Prediction model, oral heath, development, validation, machine learning
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
