• Dr S.Chandra Sekaran
• B.Neelu
• M.Murali

In recent times most of the babies are delivered preterm due to various factors. The risk of complication for premature newborns are increased in future (example: brain problem, breathing problem, hearing problem etc.,). Sometimes infant mortality rate increased due to Preterm or premature birth. There is a need to predict preterm birth earlier is necessary. To analyze the data of preterm birth only with medical data predictive analytics is gives the partial insights about preterm birth. In addition to that mother’s clinical data, the behavioral, psychological, environmental circumstances data needs to integrated to analyze and design a prognostic model to prevent and predict preterm birth. In this paper we will proposed that cross domain data fusion prognostic model that use the multiple domain data other than medial data is fused to predict the pattern of preterm birth, with the big data classification algorithm techniques gives the best accuracy of predicting preterm birth.

Preterm birth, big data, crosses domain data fusion, classification algorithm, data integration, and predictive analytics

"PRETERERM BIRTH PROGNOSTIC PREDICTION USING CROSS DOMAIN DATA FUSION", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 5, page no.193-200, May-2024, Available :http://www.jetir.org/papers/JETIRGG06031.pdf

"PRETERERM BIRTH PROGNOSTIC PREDICTION USING CROSS DOMAIN DATA FUSION", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 5, page no. pp193-200, May-2024, Available at : http://www.jetir.org/papers/JETIRGG06031.pdf