Prediction of Clinicians' Treatment in Preterm Infants with Suspected Late-onset Sepsis - An ML Approach

被引：0

作者：

Hu, Yifei ^{[1
]}

Lee, Vincent. C. S. ^{[1
]}

Tan, Kenneth ^{[2
]}

机构：

[1] Monash Univ, Fac Informat Technol, Melbourne, Vic, Australia

[2] Monash Children Hosp, Monash Newborn Clin Dept, Melbourne, Vic, Australia

来源：

PROCEEDINGS OF THE 2018 13TH IEEE CONFERENCE ON INDUSTRIAL ELECTRONICS AND APPLICATIONS (ICIEA 2018) | 2018年

关键词：

machine learning; neonatal sepsis; prediction; vital signs;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

As a prevalent disease of preterm infants, lateonset neonatal sepsis has taken up a huge proportion of morbidity and mortality of newborn babies. We have been continuously capturing vital signs of preterm infants in NICU, and proposed a non-invasive method based on machine learning techniques to predict the clinicians' treatment on them. Then we provide evaluation of predictive models and prove their feasibility. Our models could help the pediatricians make wiser clinical decision, such as more accurate treatment, avoiding the abuse of antibiotics to some extent.

引用

页码：1177 / 1182

页数：6

共 13 条

[1]

Agrawal R., 1995, VLDB '95. Proceedings of the 21st International Conference on Very Large Data Bases, P490

[2]

D. of H. & H. Services, SEPS IN NEON

[3]

Das G, 1997, LECT NOTES ARTIF INT, V1263, P88

[4] An introduction to ROC analysis [J].

Fawcett, Tom .

PATTERN RECOGNITION LETTERS, 2006, 27 (08) :861-874

[5] Heart rate characteristics: Novel physiomarkers to predict neonatal infection and death [J].

Griffin, MP ;

Lake, DE ;

Bissonette, EA ;

Harrell, FE ;

O'Shea, TM ;

Moorman, JR .

PEDIATRICS, 2005, 116 (05) :1070-1074

[6] Early and late onset sepsis in very-low-birth-weight infants from a large group of neonatal intensive care units [J].

Hornik, C. P. ;

Fort, P. ;

Clark, R. H. ;

Watt, K. ;

Benjamin, D. K., Jr. ;

Smith, P. B. ;

Manzoni, P. ;

Jacqz-Aigrain, E. ;

Kaguelidou, F. ;

Cohen-Wolkowiez, M. .

EARLY HUMAN DEVELOPMENT, 2012, 88 :S69-S74

[7]

Ling Lin, 1998, Proceedings of the Twenty-Fourth International Conference on Very-Large Databases, P170

[8] Medical decision support using machine learning for early detection of late-onset neonatal sepsis [J].

Mani, Subramani ;

Ozdas, Asli ;

Aliferis, Constantin ;

Varol, Huseyin Atakan ;

Chen, Qingxia ;

Carnevale, Randy ;

Chen, Yukun ;

Romano-Keeler, Joann ;

Nian, Hui ;

Weitkamp, Joern-Hendrik .

JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION, 2014, 21 (02) :326-336

[9] A case definition for national and international neonatal bloodstream infection surveillance [J].

Modi, N. ;

Dore, C. J. ;

Saraswatula, A. ;

Richards, M. ;

Bamford, K. B. ;

Coello, R. ;

Holmes, A. .

ARCHIVES OF DISEASE IN CHILDHOOD-FETAL AND NEONATAL EDITION, 2009, 94 (01) :F8-F12

[10]

Pedregosa F, 2011, J MACH LEARN RES, V12, P2825

← 1 2 →