{"ID":2853826,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2510.15218","arxiv_id":"2510.15218","title":"Ensemble Deep Learning Models for Early Detection of Meningitis in ICU: Multi-center Study","abstract":"The stacking ensemble combining RF, LightGBM, and DNN performed well on internal test sets, exhibiting an NPV greater than 99.9% even with substantial class imbalance. While performance was lower on the external eICU cohort compared to the internal test sets, sensitivity remained robust. Therefore, the stacking ensemble may serve as a rule-out screening option for ERs and ICUs after additional prospective multi-site validation studies for its efficacy in real-world.","short_abstract":"The stacking ensemble combining RF, LightGBM, and DNN performed well on internal test sets, exhibiting an NPV greater than 99.9% even with substantial class imbalance. While performance was lower on the external eICU cohort compared to the internal test sets, sensitivity remained robust. Therefore, the stacking ensembl...","url_abs":"https://arxiv.org/abs/2510.15218","url_pdf":"https://arxiv.org/pdf/2510.15218v3","authors":"[\"Han Ouyang\",\"Ayush Singhal\",\"Jesse Hamilton\",\"Saeed Amal\"]","published":"2025-10-17T00:56:47Z","proceeding":"cs.LG","tasks":"[\"cs.LG\"]","methods":"[]","has_code":false}