A Tag-Based Data Model for Privacy-Preserving Medical Applications

Privacy-preserving contact tracing in 5G-integrated and blockchain-based medical applications

Computer Standards & Interfaces ◽

10.1016/j.csi.2021.103520 ◽

2021 ◽

Vol 77 ◽

pp. 103520

Author(s):

Can Zhang ◽

Chang Xu ◽

Kashif Sharif ◽

Liehuang Zhu

Keyword(s):

Privacy Preserving ◽

Contact Tracing ◽

Medical Applications

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On the Fairness of Privacy-Preserving Representations in Medical Applications

Domain Adaptation and Representation Transfer, and Distributed and Collaborative Learning - Lecture Notes in Computer Science ◽

10.1007/978-3-030-60548-3_14 ◽

2020 ◽

pp. 140-149

Author(s):

Mhd Hasan Sarhan ◽

Nassir Navab ◽

Abouzar Eslami ◽

Shadi Albarqouni

Keyword(s):

Privacy Preserving ◽

Medical Applications

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Implementation of Client Controlled Privacy Preserving Data Model for Mining Decision Rules using Decision Tree and Association Rules

International Journal of Innovative Technology and Exploring Engineering - Special Issue ◽

10.35940/ijitee.a4614.119119 ◽

2019 ◽

Vol 9 (1) ◽

pp. 3617-3624

Keyword(s):

Decision Tree ◽

Data Model ◽

Association Rule ◽

Association Rule Mining ◽

Decision Rules ◽

Privacy Preserving ◽

Rule Mining ◽

Data Owner ◽

Higher Dimensional ◽

Near Future

The privacy-preserving data mining (PPDM) is one of the techniques which are used for mining data dynamically with preserving privacy of the end data owner. In this paper, a PPDM technique for generating the privacy-preserving decision rules is proposed and implemented. The key motive of presenting this privacy-preserving decision rule mining technique is to demonstrate how securely data is aggregated in the PPDM environment, how securely extract them and consumed them with the help of applications. In addition to comparing the state of art methods for mining privacy preserving decision rules for preparing the future directions of research. Therefore two different data models have used namely decision tree and association rule mining. The conducted experiments demonstrate that decision tree-based techniques are superior to the association rule mining based techniques for mining higher dimensional data with higher accuracy and low resource consumption. Therefore in the near future for extending this data model the two concepts are also introduced in this paper.

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Review of Research, Comparisons and Medical Applications of Ericksonian Techniques.

Contemporary Psychology ◽

10.1037/028304 ◽

1990 ◽

Vol 35 (2) ◽

pp. 185-185

Author(s):

Paul L. Wachtel

Keyword(s):

Medical Applications

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Decision Making in Team Sports: Data, model and applied perspective

PsycEXTRA Dataset ◽

10.1037/e509992008-001 ◽

2008 ◽

Author(s):

Pedro J. M. Passos ◽

Duarte Araujo ◽

Keith Davids ◽

Ana Diniz ◽

Luis Gouveia ◽

...

Keyword(s):

Decision Making ◽

Data Model ◽

Team Sports ◽

Sports Data

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SARI : A User-Oriented Data Bank System for Medical Applications

Methods of Information in Medicine ◽

10.1055/s-0038-1635729 ◽

1976 ◽

Vol 15 (02) ◽

pp. 69-74

Author(s):

M. Goldberg ◽

B. Doyon

Keyword(s):

Data Base ◽

Personal Data ◽

Data Bank ◽

Medical Applications ◽

Basic Principles ◽

Base Management ◽

General Data ◽

Privacy Problem ◽

Bank System ◽

Made In

This paper describes a general data base management package, devoted to medical applications. SARI is a user-oriented system, able to take into account applications very different by their nature, structure, size, operating procedures and general objectives, without any specific programming. It can be used in conversational mode by users with no previous knowledge of computers, such as physicians or medical clerks.As medical data are often personal data, the privacy problem is emphasized and a satisfactory solution implemented in SARI.The basic principles of the data base and program organization are described ; specific efforts have been made in order to increase compactness and to make maintenance easy.Several medical applications are now operational with SARI. The next steps will mainly consist in the implementation of highly sophisticated functions.

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A Qualified Assertion Database for the History of Places

International Journal of Humanities and Arts Computing ◽

10.3366/ijhac.2019.0233 ◽

2019 ◽

Vol 13 (1-2) ◽

pp. 95-115

Author(s):

Brandon Plewe

Keyword(s):

Data Model ◽

Temporal Change ◽

Religious Congregations ◽

Historical Gis ◽

The Past ◽

Model Based ◽

Complex Information ◽

Invaluable Tool ◽

History Of ◽

The Rich

Historical place databases can be an invaluable tool for capturing the rich meaning of past places. However, this richness presents obstacles to success: the daunting need to simultaneously represent complex information such as temporal change, uncertainty, relationships, and thorough sourcing has been an obstacle to historical GIS in the past. The Qualified Assertion Model developed in this paper can represent a variety of historical complexities using a single, simple, flexible data model based on a) documenting assertions of the past world rather than claiming to know the exact truth, and b) qualifying the scope, provenance, quality, and syntactics of those assertions. This model was successfully implemented in a production-strength historical gazetteer of religious congregations, demonstrating its effectiveness and some challenges.

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