Empowering Mother, Child and Seniors: AI-Driven Healthcare for all
Transforming Healthcare with Cloud and AI Innovation
Boston, Bhubaneswar and Rourkela
Transforming Healthcare with Cloud and AI Innovation
Boston, Bhubaneswar and Rourkela
Machine Learning Models to Predict Preterm Birth Risk
This allows for early intervention strategies to be implemented, potentially reducing the incidence of preterm births and improving neonatal outcomes. For example, a study could utilize machine learning to analyze electronic health records (EHRs), identifying risk factors such as maternal age, previous preterm births, pregnancy complications, and lifestyle factors that significantly contribute to preterm birth risks.
Deep Learning for Customized Pharmacological Interventions
This approach minimizes trial and error in medication selection, reduces the risk of adverse reactions, and increases the likelihood of preventing preterm labor. For instance, an AI model could recommend the optimal dosage of progesterone supplements for a patient based on her specific risk factors and genetic markers, thus providing a tailored approach to preventing preterm labor.
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