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Predictive Patient-Centric Healthcare: A Novel Algorithm for Recommending Learning Applications

Predictive Patient-Centric Healthcare: A Novel Algorithm for Recommending Learning Applications

Ajay B. Gadicha, Vijay B. Gadicha, Mohammad Zuhair
Copyright: © 2024 |Pages: 14
ISBN13: 9781668495964|ISBN10: 1668495961|ISBN13 Softcover: 9781668495971|EISBN13: 9781668495988
DOI: 10.4018/978-1-6684-9596-4.ch007
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MLA

Gadicha, Ajay B., et al. "Predictive Patient-Centric Healthcare: A Novel Algorithm for Recommending Learning Applications." Futuristic e-Governance Security With Deep Learning Applications, edited by Rajeev Kumar, et al., IGI Global, 2024, pp. 139-152. https://doi.org/10.4018/978-1-6684-9596-4.ch007

APA

Gadicha, A. B., Gadicha, V. B., & Zuhair, M. (2024). Predictive Patient-Centric Healthcare: A Novel Algorithm for Recommending Learning Applications. In R. Kumar, A. Abdul Hamid, N. Inayah Binti Ya’akub, M. Sharma Gaur, & S. Kumar (Eds.), Futuristic e-Governance Security With Deep Learning Applications (pp. 139-152). IGI Global. https://doi.org/10.4018/978-1-6684-9596-4.ch007

Chicago

Gadicha, Ajay B., Vijay B. Gadicha, and Mohammad Zuhair. "Predictive Patient-Centric Healthcare: A Novel Algorithm for Recommending Learning Applications." In Futuristic e-Governance Security With Deep Learning Applications, edited by Rajeev Kumar, et al., 139-152. Hershey, PA: IGI Global, 2024. https://doi.org/10.4018/978-1-6684-9596-4.ch007

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Abstract

In this chapter, the authors propose a novel recommendation algorithm for patient-centric healthcare that utilizes learning applications. The algorithm aims to predict and recommend suitable learning applications to patients based on their individual needs and preferences. By leveraging machine learning techniques and patient data, the algorithm analyzes various factors such as medical history, demographics, and personal interests to generate personalized recommendations. This patient-centric approach enhances the healthcare experience by empowering patients to actively engage in their own health management and education. The algorithm's effectiveness is evaluated through experiments and comparisons with existing recommendation methods, demonstrating its potential to improve patient outcomes and overall healthcare quality.

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