Optimizing Patient Outcomes with AI and Predictive Analytics in Healthcare

Abstract

Healthcare's integration with the emerging artificial intelligence, predictive analytics and health information exchange (HIE) system is currently undergoing a revolution. These emerging technologies are offering better diagnostic accuracies, more personalized treatments, and better patients' outcomes. Artificial Intelligence supported by data from either Electronic Health Records or other big data sources are increasing the accuracy of forecasting critical patient conditions such as disease developments, hospital readmission rates, and mortality risks in patients. These AI-empowered models ensure seamless data sharing between the care providers and promote operational interoperability. Challenges to overcome include issues of privacy of the data, the biases of the prediction algorithms, and the proper integration of the model into the currently established operational environments of healthcare providers. With these technologies combined, it will become possible to optimize patient's outcomes with the provision of data to empower real-time medical interventions.

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