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Amplifying the Privacy Protection for the Distributed, Structured, and Concerted Data in the Healthcare

Year: 2024

Type: article

Abstract: Machine learning has gained significant importance in healthcare for enhancing decision- making and improving predictions. However, healthcare data is often distributed across various locations, such as multiple hospitals, which presents a challenge in analyzing this data while protecting sensitive personal information. A new approach ensures privacy during data analysis. We describe the implementation of this method and evaluate its performance using medical datasets. Our method demonstrates how machine learning can be applied to sensitive healthcare data while protecting and safeguarding the privacy.

Source: INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT

DOI: 10.55041/ijsrem39499

Authors: K. Ajay, K. Sathvika, M. Pavan Kumar, Arun Singh Kaurav

Institution: Guru Nanak Institutions

Language: English

Topic: Privacy-Preserving Technologies in Data

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

SDG: Good health and well-being

Open Access status: bronze

OpenAlex ID: W4405097674

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