Clara Schaarup, Louise Bilenberg Pape-Haugaard, Ole Kristian Hejlesen
Models Used in Clinical Decision Support Systems Supporting Healthcare Professionals Treating Chronic Wounds: Systematic Literature Review
JMIR diabetes
intraoperative hypotension lead postoperative organ dysfunction previous studies primarily used invasive arterial pressure key biosignal detection hypotension however studies limitations incorporating different biosignal modalities utilizing periodic nature biosignals address limitations utilized frequencydomain information provides key insights timedomain analysis cannot provide revealed recent advances deep learning frequencydomain information propose deeplearning approach integrates multiple biosignal modalities used discrete fourier transform technique extract frequency information biosignal data combined original timedomain data input deep learning model improve interpretability results incorporated recent interpretable modules deeplearning models analysis constructed 75994 segments data 3226 patients predict hypotension surgery proposed frequencydomain deeplearning model outperformed conventional approaches rely solely timedomain information notably model achieved greater increase auroc performance timedomain deep learning models trained noninvasive biosignal data auroc 0898 95 ci 0885091 vs 0853 95 ci 08390867 analysis revealed 1530 hz frequency band played important role predicting hypotension events utilizing frequency domain demonstrated high performance invasive data also showed significant performance improvement applied noninvasive data alone proposed framework offers clinicians novel perspective predicting intraoperative hypotension