SHAP Algorithm for Healthcare Data Classification

Samson Mihirette; Qing Tan

doi:10.1007/978-3-031-15471-3_31

SHAP Algorithm for Healthcare Data Classification

Samson Mihirette, Qing Tan

School of Computing and Information systems

Athabasca University

Research output: Chapter in Book/Report/Conference proceeding › Published Conference contribution › peer-review

1 Citation (Scopus)

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.

Original language	English
Title of host publication	Hybrid Artificial Intelligent Systems - 17th International Conference, HAIS 2022, Proceedings
Editors	Pablo García Bringas, Hilde Pérez García, Francisco Javier Martínez de Pisón, José Ramón Villar Flecha, Alicia Troncoso Lora, Enrique A. de la Cal, Alvaro Herrero, Francisco Martínez Álvarez, Giuseppe Psaila, Hector Quintián, Emilio Corchado
Pages	363-374
Number of pages	12
DOIs	https://doi.org/10.1007/978-3-031-15471-3_31
Publication status	Published - 2022
Event	17th International Conference on Hybrid Artificial Intelligence Systems, HAIS 2022 - Salamancaa, Spain Duration: 5 Sep. 2022 → 7 Sep. 2022

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	13469 LNAI
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	17th International Conference on Hybrid Artificial Intelligence Systems, HAIS 2022
Country/Territory	Spain
City	Salamancaa
Period	5/09/22 → 7/09/22

Keywords

Data privacy
Data privacy broker
Healthcare Information System (HIS)
SHAP

Access to Document

10.1007/978-3-031-15471-3_31

Cite this

Mihirette, S., & Tan, Q. (2022). SHAP Algorithm for Healthcare Data Classification. In P. García Bringas, H. Pérez García, F. J. Martínez de Pisón, J. R. Villar Flecha, A. Troncoso Lora, E. A. de la Cal, A. Herrero, F. Martínez Álvarez, G. Psaila, H. Quintián, & E. Corchado (Eds.), Hybrid Artificial Intelligent Systems - 17th International Conference, HAIS 2022, Proceedings (pp. 363-374). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 13469 LNAI). https://doi.org/10.1007/978-3-031-15471-3_31

Mihirette, Samson ; Tan, Qing. / SHAP Algorithm for Healthcare Data Classification. Hybrid Artificial Intelligent Systems - 17th International Conference, HAIS 2022, Proceedings. editor / Pablo García Bringas ; Hilde Pérez García ; Francisco Javier Martínez de Pisón ; José Ramón Villar Flecha ; Alicia Troncoso Lora ; Enrique A. de la Cal ; Alvaro Herrero ; Francisco Martínez Álvarez ; Giuseppe Psaila ; Hector Quintián ; Emilio Corchado. 2022. pp. 363-374 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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title = "SHAP Algorithm for Healthcare Data Classification",

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.",

keywords = "Data privacy, Data privacy broker, Healthcare Information System (HIS), SHAP",

author = "Samson Mihirette and Qing Tan",

note = "Publisher Copyright: {\textcopyright} 2022, Springer Nature Switzerland AG.; 17th International Conference on Hybrid Artificial Intelligence Systems, HAIS 2022 ; Conference date: 05-09-2022 Through 07-09-2022",

year = "2022",

doi = "10.1007/978-3-031-15471-3_31",

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series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

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editor = "{Garc{\'i}a Bringas}, Pablo and {P{\'e}rez Garc{\'i}a}, Hilde and {Mart{\'i}nez de Pis{\'o}n}, {Francisco Javier} and {Villar Flecha}, {Jos{\'e} Ram{\'o}n} and {Troncoso Lora}, Alicia and {de la Cal}, {Enrique A.} and Alvaro Herrero and {Mart{\'i}nez {\'A}lvarez}, Francisco and Giuseppe Psaila and Hector Quinti{\'a}n and Emilio Corchado",

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Mihirette, S & Tan, Q 2022, SHAP Algorithm for Healthcare Data Classification. in P García Bringas, H Pérez García, FJ Martínez de Pisón, JR Villar Flecha, A Troncoso Lora, EA de la Cal, A Herrero, F Martínez Álvarez, G Psaila, H Quintián & E Corchado (eds), Hybrid Artificial Intelligent Systems - 17th International Conference, HAIS 2022, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 13469 LNAI, pp. 363-374, 17th International Conference on Hybrid Artificial Intelligence Systems, HAIS 2022, Salamancaa, Spain, 5/09/22. https://doi.org/10.1007/978-3-031-15471-3_31

SHAP Algorithm for Healthcare Data Classification. / Mihirette, Samson; Tan, Qing.
Hybrid Artificial Intelligent Systems - 17th International Conference, HAIS 2022, Proceedings. ed. / Pablo García Bringas; Hilde Pérez García; Francisco Javier Martínez de Pisón; José Ramón Villar Flecha; Alicia Troncoso Lora; Enrique A. de la Cal; Alvaro Herrero; Francisco Martínez Álvarez; Giuseppe Psaila; Hector Quintián; Emilio Corchado. 2022. p. 363-374 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 13469 LNAI).

Research output: Chapter in Book/Report/Conference proceeding › Published Conference contribution › peer-review

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T1 - SHAP Algorithm for Healthcare Data Classification

AU - Mihirette, Samson

AU - Tan, Qing

PY - 2022

Y1 - 2022

N2 - 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.

AB - 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.

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KW - Data privacy broker

KW - Healthcare Information System (HIS)

KW - SHAP

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AN - SCOPUS:85139053304

SN - 9783031154706

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 363

EP - 374

BT - Hybrid Artificial Intelligent Systems - 17th International Conference, HAIS 2022, Proceedings

A2 - García Bringas, Pablo

A2 - Pérez García, Hilde

A2 - Martínez de Pisón, Francisco Javier

A2 - Villar Flecha, José Ramón

A2 - Troncoso Lora, Alicia

A2 - de la Cal, Enrique A.

A2 - Herrero, Alvaro

A2 - Martínez Álvarez, Francisco

A2 - Psaila, Giuseppe

A2 - Quintián, Hector

A2 - Corchado, Emilio

T2 - 17th International Conference on Hybrid Artificial Intelligence Systems, HAIS 2022

Y2 - 5 September 2022 through 7 September 2022

ER -

Mihirette S, Tan Q. SHAP Algorithm for Healthcare Data Classification. In García Bringas P, Pérez García H, Martínez de Pisón FJ, Villar Flecha JR, Troncoso Lora A, de la Cal EA, Herrero A, Martínez Álvarez F, Psaila G, Quintián H, Corchado E, editors, Hybrid Artificial Intelligent Systems - 17th International Conference, HAIS 2022, Proceedings. 2022. p. 363-374. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-031-15471-3_31

SHAP Algorithm for Healthcare Data Classification

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