SHAP Algorithm for Healthcare Data Classification

To strengthen the healthcare data privacy protecting techniques and ensure the transparency of healthcare data exchange, many data privacy-preserving methods have been introduced. This paper highlights privacy concerns and introduces techniques and research directions towards data privacy in Healthc...

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Published inHybrid Artificial Intelligent Systems Vol. 13469; pp. 363 - 374
Main Authors Mihirette, Samson, Tan, Qing
Format Book Chapter
LanguageEnglish
Published Switzerland Springer International Publishing AG 2022
Springer International Publishing
SeriesLecture Notes in Computer Science
Subjects
Online AccessGet full text
ISBN9783031154706
3031154703
ISSN0302-9743
1611-3349
DOI10.1007/978-3-031-15471-3_31

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Abstract To strengthen the healthcare data privacy protecting techniques and ensure the transparency of healthcare data exchange, many data privacy-preserving methods have been introduced. This paper highlights privacy concerns and introduces techniques and research directions towards data privacy in Healthcare Information Systems (HIS). The paper demonstrates the use and the power of the Shapley Additive exPlanations (SHAP) algorithm to identify and classify critical data elements that can put personal privacy at risk within a dataset. A conceptual patient-centric healthcare information system architecture with a data broker is proposed in this paper. The proposed architecture also includes the privacy broker that leverages application programming interface services and integration middleware in safeguarding healthcare data privacy.
AbstractList To strengthen the healthcare data privacy protecting techniques and ensure the transparency of healthcare data exchange, many data privacy-preserving methods have been introduced. This paper highlights privacy concerns and introduces techniques and research directions towards data privacy in Healthcare Information Systems (HIS). The paper demonstrates the use and the power of the Shapley Additive exPlanations (SHAP) algorithm to identify and classify critical data elements that can put personal privacy at risk within a dataset. A conceptual patient-centric healthcare information system architecture with a data broker is proposed in this paper. The proposed architecture also includes the privacy broker that leverages application programming interface services and integration middleware in safeguarding healthcare data privacy.
Author Tan, Qing
Mihirette, Samson
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Villar Flecha, José Ramón
Troncoso Lora, Alicia
de la Cal, Enrique A
García Bringas, Pablo
Psaila, Giuseppe
Martínez Álvarez, Francisco
Quintián, Héctor
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Snippet To strengthen the healthcare data privacy protecting techniques and ensure the transparency of healthcare data exchange, many data privacy-preserving methods...
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SourceType Publisher
StartPage 363
SubjectTerms Data privacy
Data privacy broker
Healthcare Information System (HIS)
SHAP
Title SHAP Algorithm for Healthcare Data Classification
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