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To help with this algorithm

 A recent research paper on policy tried to address this issue through Machine Learning (ML), methods for identifying the most important investments that can assist Bangladesh in speeding its progress toward RMNCH-N utilization. Despite the improvement in the RMNCH-N environment, Bangladesh hasn’t seen enough utilization of essential services such as skilled birth attendance or institutional delivery to meet its RMNCH–N objectives. In particular, there are inequities with regards to the use of services and health status among different socio-economic groups. Strategically targeted investments in the most important factors are crucial to accelerate the pace of advancement.

 To help with this algorithm, supervised ML algorithms were developed to assess the importance of demand- and supply-side factors for 19 indicators of RMNCH–N that are related to the use of services, quality treatment, and the health/nutrition outcomes. Artificial Intelligence’s subset ML mimics human learning personalityrightsdatabase personality rights database Website personality rights database com processes, and efficiently and effectively analyse historical data and intricate relationships to aid in prediction and decision making. This technique allowed for the an analysis of large data collections from health facility surveys, as well as health and demographic surveys that span 10 years.

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