Research Results from Taipei Medical University Update Knowledge of Artificial Intelligence (Artificial intelligence-assisted prediction of preeclampsia: Development and external validation of a nationwide health insurance dataset of the BPJS …)

2020 APR 29 (NewsRx) -- By a News Reporter-Staff News Editor at Insurance Daily News -- Data detailed on Artificial Intelligence have been presented. According to news reporting from Taipei, Taiwan, by NewsRx journalists, research stated, “We developed and validated an artificial intelligence (AI)-assisted prediction of preeclampsia applied to a nationwide health insurance dataset in Indonesia. The BPJS Kesehatan dataset have been preprocessed using a nested case-control design into preeclampsia/eclampsia (n=3318) and normotensive pregnant women (n=19,883) from all women with one pregnancy.”

Financial support for this research came from Ministry of Science and Technology, Taiwan.

The news correspondents obtained a quote from the research from Taipei Medical University, “The dataset provided 95 features consisting of demographic variables and medical histories started from 24 months to event and ended by delivery as the event. Six algorithms were compared by area under the receiver operating characteristics curve (AUROC) with a subgroup analysis by time to the event. We compared our model to similar prediction models from systematically reviewed studies. In addition, we conducted a text mining analysis based on natural language processing techniques to interpret our modeling results. The best model consisted of 17 predictors extracted by a random forest algorithm. Nine 12 months to the event was the period that had the best AUROC in external validation by either geographical (0.88, 95% confidence interval (CI) 0.88-0.89) or temporal split (0.86, 95% CI 0.85-0.86). We compared this model to prediction models in seven studies from 869 records in PUBMED, EMBASE, and SCOPUS. This model outperformed the previous models in terms of the precision, sensitivity, and specificity in all validation sets. Our low-cost model improved preliminary prediction to decide pregnant women that will be predicted by the models with high specificity and advanced predictors. This work was supported by grant no.”

According to the news reporters, the research concluded: “MOST108-2221-E-038-018 from the Ministry of Science and Technology of Taiwan.”

For more information on this research see: Artificial intelligence-assisted prediction of preeclampsia: Development and external validation of a nationwide health insurance dataset of the BPJS Kesehatan in Indonesia. Ebiomedicine, 2020;54():102710.

Our news journalists report that additional information may be obtained by contacting H. Sufriyana, Graduate Institute of Biomedical Informatics, College of Medical Science and Technology, Taipei Medical University, Taipei 11031, Taiwan. Additional authors for this research include Y.W. Wu and E.C Su.

The direct object identifier (DOI) for that additional information is: https://doi.org/10.1016/j.ebiom.2020.102710. This DOI is a link to an online electronic document that is either free or for purchase, and can be your direct source for a journal article and its citation.

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