FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W4386757988> ?p ?o ?g. }

• W4386757988 abstract "Background and Aim: Acute pancreatitis (AP) is potentially fatal. Therefore, early identification of patients at a high mortality risk and timely intervention are essential. This study aimed to establish an explainable machine-learning model for predicting in-hospital mortality of intensive care unit (ICU) patients with AP. Methods: Data on patients with AP, including demographics, vital signs, laboratory tests, comorbidities, treatment, complication, and severity scores, were extracted from the Medical Information Mart for Intensive Care IV (MIMIC-IV) and the eICU collaborative research database (eICU-CRD). Based on the data from MIMIC-IV, we used the least absolute shrinkage and selection operator algorithm to select variables and then established 9 machine-learning models and screened the optimal model. Data from the eICU-CRD were used for external validation. The area under the receiver operating characteristic curve (AUC), sensitivity, specificity, accuracy, decision curve, and calibration plots were used to assess the models’ efficacy. Shapley’s additive explanation values were used to explain the model. Results: Gaussian naive Bayes (GNB) model had the best performance on the data from MIMIC-IV, with an AUC, accuracy, sensitivity, and specificity of 0.840, 0.787, 0.839, and 0.792, respectively. The GNB model also performed well on the data from the eICU-CRD, with an AUC, accuracy, sensitivity, and specificity of 0.862, 0.833, 0.848, and 0.763, respectively. According to Shapley’s additive explanation values, the top 4 predictive factors were maximum red cell distribution width, minimum saturation of blood oxygen, maximum blood urea nitrogen, and the Sequential Organ Failure Assessment score. Conclusion: The GNB model demonstrated excellent performance and generalizability in predicting mortality in ICU patients with AP. Therefore, it can identify patients at a high mortality risk." @default.
• W4386757988 created "2023-09-16" @default.
• W4386757988 creator A5003924230 @default.
• W4386757988 creator A5012525075 @default.
• W4386757988 creator A5024198000 @default.
• W4386757988 creator A5029400417 @default.
• W4386757988 creator A5042978732 @default.
• W4386757988 creator A5053845074 @default.
• W4386757988 creator A5060091977 @default.
• W4386757988 creator A5061662385 @default.
• W4386757988 creator A5075944776 @default.
• W4386757988 creator A5084563934 @default.
• W4386757988 creator A5092187667 @default.
• W4386757988 date "2023-09-15" @default.
• W4386757988 modified "2023-09-26" @default.
• W4386757988 title "Prediction of in-hospital Mortality of Intensive Care Unit Patients with Acute Pancreatitis Based on an Explainable Machine Learning Algorithm" @default.
• W4386757988 cites W1973186375 @default.
• W4386757988 cites W1974784146 @default.
• W4386757988 cites W1997731007 @default.
• W4386757988 cites W2025619691 @default.
• W4386757988 cites W2048110056 @default.
• W4386757988 cites W2099716924 @default.
• W4386757988 cites W2139253803 @default.
• W4386757988 cites W2145758369 @default.
• W4386757988 cites W2168925860 @default.
• W4386757988 cites W2794058441 @default.
• W4386757988 cites W2804314749 @default.
• W4386757988 cites W2811115492 @default.
• W4386757988 cites W2916544798 @default.
• W4386757988 cites W2947233445 @default.
• W4386757988 cites W2970366021 @default.
• W4386757988 cites W2990895485 @default.
• W4386757988 cites W3091931331 @default.
• W4386757988 cites W3123195699 @default.
• W4386757988 cites W3126598488 @default.
• W4386757988 cites W3156037271 @default.
• W4386757988 cites W3199053037 @default.
• W4386757988 cites W4200451151 @default.
• W4386757988 cites W4211258447 @default.
• W4386757988 cites W4249270402 @default.
• W4386757988 cites W4295185371 @default.
• W4386757988 cites W4309457645 @default.
• W4386757988 doi "https://doi.org/10.1097/mcg.0000000000001910" @default.
• W4386757988 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/37712768" @default.
• W4386757988 hasPublicationYear "2023" @default.
• W4386757988 type Work @default.
• W4386757988 citedByCount "0" @default.
• W4386757988 crossrefType "journal-article" @default.
• W4386757988 hasAuthorship W4386757988A5003924230 @default.
• W4386757988 hasAuthorship W4386757988A5012525075 @default.
• W4386757988 hasAuthorship W4386757988A5024198000 @default.
• W4386757988 hasAuthorship W4386757988A5029400417 @default.
• W4386757988 hasAuthorship W4386757988A5042978732 @default.
• W4386757988 hasAuthorship W4386757988A5053845074 @default.
• W4386757988 hasAuthorship W4386757988A5060091977 @default.
• W4386757988 hasAuthorship W4386757988A5061662385 @default.
• W4386757988 hasAuthorship W4386757988A5075944776 @default.
• W4386757988 hasAuthorship W4386757988A5084563934 @default.
• W4386757988 hasAuthorship W4386757988A5092187667 @default.
• W4386757988 hasConcept C11413529 @default.
• W4386757988 hasConcept C119857082 @default.
• W4386757988 hasConcept C126322002 @default.
• W4386757988 hasConcept C151956035 @default.
• W4386757988 hasConcept C154945302 @default.
• W4386757988 hasConcept C177713679 @default.
• W4386757988 hasConcept C194828623 @default.
• W4386757988 hasConcept C2776376669 @default.
• W4386757988 hasConcept C2776670229 @default.
• W4386757988 hasConcept C2987404301 @default.
• W4386757988 hasConcept C41008148 @default.
• W4386757988 hasConcept C58471807 @default.
• W4386757988 hasConcept C71924100 @default.
• W4386757988 hasConcept C76318530 @default.
• W4386757988 hasConceptScore W4386757988C11413529 @default.
• W4386757988 hasConceptScore W4386757988C119857082 @default.
• W4386757988 hasConceptScore W4386757988C126322002 @default.
• W4386757988 hasConceptScore W4386757988C151956035 @default.
• W4386757988 hasConceptScore W4386757988C154945302 @default.
• W4386757988 hasConceptScore W4386757988C177713679 @default.
• W4386757988 hasConceptScore W4386757988C194828623 @default.
• W4386757988 hasConceptScore W4386757988C2776376669 @default.
• W4386757988 hasConceptScore W4386757988C2776670229 @default.
• W4386757988 hasConceptScore W4386757988C2987404301 @default.
• W4386757988 hasConceptScore W4386757988C41008148 @default.
• W4386757988 hasConceptScore W4386757988C58471807 @default.
• W4386757988 hasConceptScore W4386757988C71924100 @default.
• W4386757988 hasConceptScore W4386757988C76318530 @default.
• W4386757988 hasLocation W43867579881 @default.
• W4386757988 hasLocation W43867579882 @default.
• W4386757988 hasOpenAccess W4386757988 @default.
• W4386757988 hasPrimaryLocation W43867579881 @default.
• W4386757988 hasRelatedWork W14719196 @default.
• W4386757988 hasRelatedWork W1551601049 @default.
• W4386757988 hasRelatedWork W2057472247 @default.
• W4386757988 hasRelatedWork W2152951948 @default.
• W4386757988 hasRelatedWork W2932411505 @default.
• W4386757988 hasRelatedWork W3030120955 @default.
• W4386757988 hasRelatedWork W3032662949 @default.
• W4386757988 hasRelatedWork W4249401890 @default.
• W4386757988 hasRelatedWork W4324114517 @default.

• next