A Comprehensive Review on Smart Decision Support Systems for Health Care

被引:94
作者
Moreira, Mario W. L. [1 ,2 ]
Rodrigues, Joel J. P. C. [2 ,3 ,4 ,5 ]
Korotaev, Valery [4 ]
Al-Muhtadi, Jalal [5 ]
Kumar, Neeraj [6 ]
机构
[1] Inst Fed Educ Ciencia & Tecnol Ceara, BR-62800000 Aracati, CE, Brazil
[2] Univ Beira Interior, Inst Telecomunicacoes, P-6200161 Covilha, Portugal
[3] Natl Inst Telecommun, BR-37540000 Santa Rita Do Sapucai, MG, Brazil
[4] ITMO Univ, St Petersburg 197101, Russia
[5] King Saud Univ, Coll Comp & Informat Sci, Riyadh 12372, Saudi Arabia
[6] Thapar Univ, Dept Comp Sci & Engn, Patiala 147003, Punjab, India
来源
IEEE SYSTEMS JOURNAL | 2019年 / 13卷 / 03期
关键词
Applications; data mining (DM); decision-making; health care; smart decision support systems (DSSs) technologies; MANAGEMENT; CLASSIFICATION; IMPLEMENTATION; ENVIRONMENT; PREDICTION; FRAMEWORK; SERVICE; QUALITY; DESIGN; MODEL;
D O I
10.1109/JSYST.2018.2890121
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Medical activity requires responsibility not only based on knowledge and clinical skills, but also in managing a vast amount of information related to patient care. It is through the appropriate treatment of information that experts can consistently build a strong policy of welfare. The primary goal of decision support systems (DSSs) is to give information to the experts where and when it is needed. These systems provide knowledge, models, and data processing tools to help the experts make better decisions in several situations. They aim to resolve several problems in health services to help patients and their families manage their health care by providing better access to these services. This paper presents a deep review of the state of the art of smart DSSs. It also elaborates on the latest developments in intelligent systems to support decision-makers in health care. The most promising findings brought in literature are analyzed and summarized according to their taxonomy, application area, year of publication, and the approaches and technologies used. Smart systems can assist decisionmakers to improve the effectiveness of their decisions using the integration of data mining techniques and model-based systems. It significantly improves the current approaches, enabling the combination of knowledge from experts and knowledge extracted from data.
引用
收藏
页码:3536 / 3545
页数:10
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