Pilot deployment of a cloud-based universal medical image repository in a large public health system: A protocol study

被引:0
|
作者
Pacheco, Viviane Margarida Gomes [1 ,3 ]
Paiva, Joselisa Peres Queiroz [1 ]
Furriel, Brunna Carolinne Rocha Silva [1 ,2 ]
Santos, Paulo Victor [1 ,2 ]
Ferreira Jr, Jose Raniery [1 ]
Reis, Marcio Rodrigues Cunha [1 ,3 ]
Tornieri, Daniel [1 ]
Ribeiro, Guilherme Alberto Sousa [1 ]
Silva, Luan Oliveira [1 ]
Nogueira, Solange Amorim [1 ]
Loureiro, Rafael Maffei [1 ]
Calixto, Wesley Pacheco [2 ,3 ]
机构
[1] Hosp Israelita Albert Einstein, Sao Paulo, Brazil
[2] Univ Fed Goias, Elect Mech & Comp Engn Sch, Goiania, Brazil
[3] Fed Inst Goias, Technol Res & Dev Ctr GCITE, Goiania, GO, Brazil
来源
PLOS ONE | 2024年 / 19卷 / 08期
关键词
MANAGEMENT; IMPLEMENTATION; BENEFITS; HISTORY; DESIGN;
D O I
10.1371/journal.pone.0307022
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
This paper outlines the protocol for the deployment of a cloud-based universal medical image repository system. The proposal aims not only at the deployment but also at the automatic expansion of the platform, incorporating Artificial Intelligence (AI) for the analysis of medical image examinations. The methodology encompasses efficient data management through a universal database, along with the deployment of various AI models designed to assist in diagnostic decision-making. By presenting this protocol, the goal is to overcome technical challenges and issues that impact all phases of the workflow, from data management to the deployment of AI models in the healthcare sector. These challenges include ethical considerations, compliance with legal regulations, establishing user trust, and ensuring data security. The system has been deployed, with a tested and validated proof of concept, possessing the capability to receive thousands of images daily and to sustain the ongoing deployment of new AI models to expedite the analysis process in medical image exams.
引用
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页数:23
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