Patient data is often scattered across systems, making it difficult to build a comprehensive picture of a patient’s health and future outcomes. Patient Outcome Prediction solutions on AWS use artificial intelligence and machine learning (AI/ML) and natural language processing (NLP) on de-identified, longitudinal patient data to discover patterns in a patient’s medical history. This helps life sciences organizations generate insights about patient outcomes, such as disease progression, to increase timely interventions, earlier identification of eligible treatments, and data-driven care management.

Guidance

Prescriptive architectural diagrams, sample code, and technical content

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  • Patient Outcome Prediction on AWS

    This Guidance helps life sciences customers to gain a comprehensive understanding of the patient care journey through a Patient Outcome Predictor (POP) application that applies artificial intelligence and machine learning (AI/ML) to de-identified, longitudinal patient data.

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