Der Schmerz
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The objective recording of subjectively experienced pain is a problem that has not been sufficiently solved to date. In recent years, data sets have been created to train artificial intelligence algorithms to recognize patterns of pain intensity. The multimodal recognition of pain with machine learning could provide a way to reduce an over- or undersupply of analgesics, explicitly in patients with limited communication skills. ⋯ Priority should be given to the multimodal approach to the recognition of pain intensity and modality compared with unimodality. Further clinical studies should clarify whether multimodal automated recognition of pain intensity and modality is in fact superior to bimodal recognition.
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The direct comparison of day care pain patients with patients from other treatment sectors with respect to sociodemographic, pain-related and psychological characteristics has not yet been the subject of systematic analyses. The project core documentation and quality assurance in pain therapy (KEDOQ-pain) of the German Pain Society (Deutsche Schmerzgesellschaft e. V.) makes this comparison possible. ⋯ The comparison of outpatients and inpatients showed significant group differences for some variables; however, the effects were very small. The evaluations suggest that pain therapy day care facilities treat a special group of pain patients that significantly differ from patients in other treatment sectors. Cautious conclusions are drawn regarding the systematic allocation of patients to care appropriate to their treatment needs.