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Optimizing Patient Outcomes Through Multi-Source Data Analysis in Healthcare

By John Joseph, Ferdin Joe

Product Image: Optimizing Patient Outcomes Through Multi-Source Data Analysis in Healthcare

Optimizing Patient Outcomes Through Multi-Source Data Analysis in Healthcare

By John Joseph, Ferdin Joe

- Default Title
Description
The landscape of healthcare is transformed by the integration of advanced data analytics, especially in the realm of multi-source data analysis. By combining diverse datasets, such as electronic health records (EHRs), genetic information, wearable device data, and patient-reported outcomes, healthcare providers can gain a comprehensive understanding of a patient's health status. This approach creates more personalized treatment plans, enhances diagnostic accuracy, and supports early detection of potential health issues. Communication between various data sources allows for the identification of hidden trends and patterns, improving predictive capabilities and optimizing patient outcomes. As healthcare systems adopt this data-driven process, it is crucial to address challenges related to data privacy, integration, and the interpretation of complex datasets, ensuring the potential benefits of multi-source data analysis are realized in ethical and effective ways. Optimizing Patient Outcomes Through Multi-Source Data Analysis in Healthcare explores the transformative potential of big data and AI in healthcare, focusing on informed decision-making. It delves into the integration of vast, diverse datasets, analyzed through AI algorithms to enhance patient outcomes and operational efficiency. This book covers topics such as automation, machine learning, and neural networks, and is a useful resource for healthcare professionals, computer engineers, business owners, academicians, researchers, and data scientists.
Product details
Binding:
Paperback
Number of Pages:
396
Release Date:
2025-04-04
Publication Date:
2025-05-28
Publisher:
IGI Global
Languages:
Original: English
ISBN13:
9798369394212
GPSR Manufacturer Reference:
[email protected]
Weight:
993 g
Height:
216 cm
Width:
280 cm
Thickness:
21 cm
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