A group decision making method to manage internal and external experts with an application to anti-lung cancer drug selection

计算机科学 群体决策 背景(考古学) 选择(遗传算法) 授权 知识管理 肺癌 风险分析(工程) 管理科学 医学 人工智能 心理学 政治学 社会心理学 工程类 内科学 法学 古生物学 生物
作者
Xiaofang Li,Huchang Liao
出处
期刊:Expert Systems With Applications [Elsevier BV]
卷期号:183: 115379-115379 被引量:16
标识
DOI:10.1016/j.eswa.2021.115379
摘要

With the changes of lifestyle and environment of people, the incidence rate of lung cancer has increased year by year, and lung cancer has become one of the most malignant tumors that threaten the health of people. Within this context, choosing appropriate anti-lung cancer drugs is of great significance for the treatment of lung cancer patients. To improve the accuracy of anti-lung cancer drug selection, it is necessary to invite many experts to participate in the evaluation process, and such a selection process can be regarded as a large-scale group decision-making problem. In existing group decision-making models, there are two hypotheses: one assumed that all experts are independent, while the other assumed that experts have certain relationships. However, in practical decision-making problems involving both internal and external experts, it is common that only some experts have mutual relationships. To address this issue, this paper proposes a large-scale group decision-making model considering the trust relationship between a set of experts. We divide experts into internal experts and external experts. The internal experts are supposed to be not independent of each other due to trust relationships, and we analyze the relationships between internal experts through the DEMATEL method. The external experts are supposed to be independent of each other. Considering the non-cooperative behaviors of experts, we provide a confidence-based adaptive consensus reaching mechanism for internal experts and a delegation-based adaptive consensus reaching mechanism for external experts. The two expert panels reach consensus through their separate consensus reaching mechanisms, and the moderator determines the optimal alternative by combining the final opinions of the two expert panels. Finally, an illustrative example about the selection of anti-non-small cell lung cancer drugs is presented to show the validity and practicality of the proposed model.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
研友_VZG7GZ应助chy采纳,获得10
刚刚
好运来发布了新的文献求助30
刚刚
1秒前
六蒙骑士发布了新的文献求助10
1秒前
1秒前
1秒前
lxl完成签到 ,获得积分10
1秒前
1秒前
独特映雁发布了新的文献求助10
1秒前
fkh完成签到,获得积分10
2秒前
小杨发布了新的文献求助10
2秒前
听安完成签到 ,获得积分10
2秒前
2秒前
2秒前
2秒前
城南发布了新的文献求助30
2秒前
晨曦完成签到,获得积分10
2秒前
hmj完成签到,获得积分10
3秒前
yeyeyeye发布了新的文献求助10
3秒前
111发布了新的文献求助10
4秒前
上官若男应助dxxx007采纳,获得10
4秒前
4秒前
4秒前
好运设计发布了新的文献求助20
5秒前
清爽四娘发布了新的文献求助10
5秒前
edna发布了新的文献求助10
5秒前
杀出个黎明举报小昊求助涉嫌违规
5秒前
慕青应助maizi采纳,获得10
5秒前
5秒前
可爱花瓣发布了新的文献求助10
6秒前
6秒前
晨曦发布了新的文献求助10
6秒前
6秒前
懵懂的采梦应助yang采纳,获得10
6秒前
不得不帅发布了新的文献求助10
6秒前
misaaaa完成签到,获得积分20
7秒前
7秒前
7秒前
清爽的曼易完成签到,获得积分10
7秒前
7秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Essentials of Carbohydrate Chemistry and Biochemistry, 4th Edition 800
Navigating Normative Orders. Interdisciplinary Perspectives 800
Organizational Behavior 510
Management and the Arts 510
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
CLSI VET01S-2024 Performance Standards for Antimicrobial Disk and Dilution Susceptibility Tests for Bacteria Isolated From Animals (7th Ed) 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 计算机科学 化学工程 工程类 有机化学 物理 复合材料 生物化学 内科学 细胞生物学 基因 遗传学 免疫学 冶金 光电子学 癌症研究
热门帖子
关注 科研通微信公众号,转发送积分 7762698
求助须知:如何正确求助?哪些是违规求助? 9307314
关于积分的说明 20299777
捐赠科研通 7347212
什么是DOI,文献DOI怎么找? 3313679
关于科研通互助平台的介绍 2463606
邀请新用户注册赠送积分活动 2327854