Clinical relevance of deep learning models in predicting the onset timing of cancer pain exacerbation.

ABSTRACT: Cancer pain is a challenging clinical problem that is encountered in the management of cancer pain. We aimed to investigate the clinical relevance of deep learning models that predict the onset of cancer pain exacerbation in hospitalized patients. We defined cancer pain exacerbation (CPE) as the pain with a numerical rating scale (NRS) score of ≥ 4. We investigated the performance of the deep learning models using the Matthews correlation coefficient (MCC) with different input lengths and time binning. All the pain records were obtained from the electronic medical records of the hematology-oncology wards in a Samsung Medical Center between July 2016 and February 2020. The model was externally validated using the holdout method with 20% of the datasets. The most common type of cancer was lu

SUBMITTER: Bang YH 

PROVIDER: S-EPMC10352236 | biostudies-literature | 2023 Jul

REPOSITORIES: biostudies-literature