Clarissa E Schilstra, Sarah J Ellis, Jennifer Cohen, Alana Gall, Abbey Diaz, Kristina Clarke, Gadiel Dumlao, Jennifer Chard, Therese M Cumming, Esther Davis, Haryana Dhillon, Mary Anne Burns, Kimberley Docking, Eng-Siew Koh, Josephine O'Reilly, Ursula M Sansom-Daly, Joanne Shaw, Nicole Speers, Natalie Taylor, Anthea Warne, Joanna E Fardell
Exploring Web-Based Information and Resources That Support Adolescents and Young Adults With Cancer to Resume Study and Work: Environmental Scan Study
JMIR cancer
clinical notes contain contextualized information beyond structured data related patients past current health status study aimed design multimodal deep learning approach improve evaluation precision hospital outcomes heart failure hf using admission clinical notes easily collected tabular data data development validation multimodal model retrospectively derived 3 openaccess us databases including medical information mart intensive care iii v14 mimiciii mimiciv v10 collected teaching hospital 2001 2019 eicu collaborative research database v12 collected 208 hospitals 2014 2015 study cohorts consisted patients critical hf clinical notes including chief complaint history present illness physical examination medical history admission medication well clinical variables recorded electronic health records analyzed developed deep learning mortality prediction model inhospital patients underwent complete internal prospective external evaluation integrated gradients shapley additive explanations shap methods used analyze importance risk factors study included 9989 164 patients development set 2497 141 patients internal validation set 1896 183 prospective validation set 7432 15 patients external validation set area receiver operating characteristic curve models 0838 95 ci 08270851 0849 95 ci 08410856 0767 95 ci 07620772 internal prospective external validation sets respectively area receiver operating characteristic curve multimodal model outperformed unimodal models test sets tabular data contributed higher discrimination medical history physical examination useful factors early assessments multimodal deep learning model combining admission notes clinical tabular data showed promising efficacy potentially novel method evaluating risk mortality patients hf providing accurate timely decision support