Feature Selection Based on a Genetic Algorithm for Optimizing Weaning Success

被引：0

作者：

Rosati, Samanta ^{[1
]}

Scotto, Andrea ^{[1
]}

Fanelli, Vito ^{[2
]}

Balestra, Gabriella ^{[1
]}

机构：

[1] Politecn Torino, Dept Elect & Telecommun, Turin, Italy

[2] Univ Torino, Dept Surg Sci, Turin, Italy

来源：

CARING IS SHARING-EXPLOITING THE VALUE IN DATA FOR HEALTH AND INNOVATION-PROCEEDINGS OF MIE 2023 | 2023年 / 302卷

关键词：

MIMIC; mechanical ventilation; weaning; genetic algorithms; feature selection;

D O I：

10.3233/SHTI230206

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

Finding the right time for weaning from ventilator is a difficult clinical decision. Several systems based on machine or deep learning are reported in literature. However, the results of these applications are not completely satisfactory and may be improved. An important aspect is represented by the features used as input of these systems. In this paper we present the results of the application of genetic algorithms to perform feature selection on a dataset containing 13688 patients under mechanical ventilation characterizing by 58 variables, extracted from the MIMIC III database. The results show that all features are important, but four of them are essential: 'Sedation_days', 'Mean_Airway_Pressure', 'PaO2', and 'Chloride'. This is only the initial step to obtain a tool to be added to the other clinical indices for minimize the risk of extubation failure.

引用

页码：566 / 570

页数：5

共 50 条

[41] Genetic Programming as a Feature Selection Algorithm
Suarez, Ranyart R.
Maria Valencia-Ramirez, Jose
Graff, Mario
2014 IEEE INTERNATIONAL AUTUMN MEETING ON POWER, ELECTRONICS AND COMPUTING (ROPEC), 2014,
[42] A Feature Selection Algorithm Based on Genetic Algorithm and Ordinal Optimization for Regression Problems
Wang, Zhaojie
Shen, Zhen
Gao, Feng
Sun, Mu
Li, Junda
Zhou, Qian
2022 IEEE 18TH INTERNATIONAL CONFERENCE ON AUTOMATION SCIENCE AND ENGINEERING (CASE), 2022, : 1609 - 1616
[43] Optimizing Feature Selection in Intrusion Detection Systems Using a Genetic Algorithm with Stochastic Universal Sampling
Akula, Radharani
Kumar, G. S. Naveen
INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS, 2025, 16 (01) : 1059 - 1068
[44] Genetic programming with a genetic algorithm for feature construction and selection
Smith M.G.
Bull L.
Genetic Programming and Evolvable Machines, 2005, 6 (3) : 265 - 281
[45] Genetic Algorithm Based Feature Selection for Detection of Surface Defects on Oranges
Thendral, R.
Suhasini, A.
JOURNAL OF SCIENTIFIC & INDUSTRIAL RESEARCH, 2016, 75 (09): : 540 - 546
[46] Hybrid feature selection based on enhanced genetic algorithm for text categorization
Ghareb, Abdullah Saeed
Abu Bakar, Azuraliza
Hamdan, Abdul Razak
EXPERT SYSTEMS WITH APPLICATIONS, 2016, 49 : 31 - 47
[47] Feature selection for target discrimination in SAR images based on Genetic Algorithm
School of Information System and Management, NUDT, Changsha 410073, China
不详
不详
不详
Tien Tzu Hsueh Pao, 2008, 6 (1041-1046):
[48] A Hybrid Approach Based on Genetic Algorithm with Ranking Aggregation for Feature Selection
Bui Quoc Trung
Le Minh Duc
Bui Thi Mai Anh
ADVANCES AND TRENDS IN ARTIFICIAL INTELLIGENCE: THEORY AND PRACTICES IN ARTIFICIAL INTELLIGENCE, 2022, 13343 : 226 - 239
[49] A Survey on Genetic Algorithm Based Feature Selection for Disease Diagnosis System
Sindhiya, S.
Gunasundari, S.
2014 IEEE INTERNATIONAL CONFERENCE ON COMPUTER COMMUNICATION AND SYSTEMS (ICCCS'14), 2014, : 164 - 169
[50] Feature selection based on hybridization of genetic algorithm and competitive swarm optimizer
Ye Ding
Kui Zhou
Weihong Bi
Soft Computing, 2020, 24 : 11663 - 11672

← 1 2 3 4 5 →