A new machine-learning method to prognosticate paraquat poisoned patients by combining coagulation, liver, and kidney indices.

ABSTRACT: The prognosis of paraquat (PQ) poisoning is highly correlated to plasma PQ concentration, which has been identified as the most important index in PQ poisoning. This study investigated the predictive value of coagulation, liver, and kidney indices in prognosticating PQ-poisoning patients, when aligned with plasma PQ concentrations. Coagulation, liver, and kidney indices were first analyzed by variance analysis, receiver operating characteristic curves, and Fisher discriminant analysis. Then, a new, intelligent, machine learning-based system was established to effectively provide prognostic analysis of PQ-poisoning patients based on a combination of the aforementioned indices. In the proposed system, an enhanced extreme learning machine wrapped with a grey wolf-optimization strategy was dev

SUBMITTER: Hu L 

PROVIDER: S-EPMC5648192 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature