Optimal Features Subset Selection for Large for Gestational Age Classification Using GridSearch Based Recursive Feature Elimination with Cross-Validation Scheme-Reference-Cited by-同舟云学术

Optimal Features Subset Selection for Large for Gestational Age Classification Using GridSearch Based Recursive Feature Elimination with Cross-Validation Scheme

Published:2020 Issue: Volume: Page:63-71
ISSN:1876-1100
Container-title:Lecture Notes in Electrical Engineering
language:
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Author:

Akhtar Faheem,Li Jianqiang,Pei Yan,Xu Yang,Rajput Asif,Wang Qing

Publisher

Springer Singapore

Link

http://link.springer.com/content/pdf/10.1007/978-981-15-3250-4_8

Reference20 articles.

1. Skou, J., Kesmodel, U., Henriksen, T.B., Secher, N.J.: An increasing proportion of infants weight more than 4000 grams at birth. Acta Obstet. Gynecol. Scand. 80(10), 931–936 (2001)

2. Das, U.S.G., Sysyn, G.D.: Abnormal fetal growth: intrauterine growth retardation, small for gestational age, large for gestational age. Pediatr. Clin. North Am. 51(3), 639–654 (2004)

3. Vasileios, G., Eleni, E., Anna, C., Dimitrios, K., Aikaterini, D., Styliani, A.: Serum adiponectin and leptin levels and insulin resistance in children born large for gestational age are affected by the degree of overweight. Clin. Endocrinol. 66(3), 353–359 (2007)

4. Langer, O.: Fetal macrosomia: etiologic factors. Clin. Obstet. Gynecol. 43(2), 283–297 (2000)

5. Battaglia, F.C., Lubchenco, L.O.: A practical classification of newborn infants by weight and gestational age. J. Pediatr. 71(2), 159–163 (1967)

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