Page 68 - ISMCON souvenir 2021

ISMSCON - 2021

Mourad et al have used machine learning and feature selection to SEER data to select the most important
features which will help doctors to make informed and optimized treatment decisions for thyroid cancer.
Zhao et al have used machine learning models to predict overall survival in patients with metastatic rectal
cancer. Lynch et al have explored the capability of unsupervised machine learning techniques for lung
cancer patient survival prediction.
References:

• Mourad, M., Moubayed, S., Dezube, A., Mourad, Y., Park, K., Torreblanca-Zanca, A., Torrecilla, J. S.,
Cancilla, J. C., & Wang, J. (2020). Machine Learning and Feature Selection Applied to SEER Data to
Reliably Assess Thyroid Cancer Prognosis. Scientific reports, 10(1), 5176.
• Zhao, B., Gabriel, R. A., Vaida, F., Lopez, N. E., Eisenstein, S., & Clary, B. M. (2020). Predicting
Overall Survival in Patients with Metastatic Rectal Cancer: a Machine Learning Approach. Journal
of gastrointestinal surgery : official journal of the Society for Surgery of the Alimentary Tract, 24(5),
1165–1172.

• Lynch, C. M., van Berkel, V. H., & Frieboes, H. B. (2017). Application of unsupervised analysis
techniques to lung cancer patient data. PloS one, 12(9), e0184370.

OS34:THE INFLUENCE OF WOMEN AUTONOMY AND DIFFERENT
SOCIO-DEMOGRAPHIC FACTORS ON THE UTILIZATION OF

DELIVERY SERVICES IN URBAN INDIA: EVIDENCE FROM

NFHS-4 , INDIA

T. B. Singh, Kritika Srivastava
Centre of Bio-Statistics, Institute of Medical Sciences, Banaras Hindu University.
Email: Kritikaamailboxx@gmail.com
Keywords: Women’s autonomy, Institutional delivery, Post Natal Care .
ABSTRACT

Maternal health refers to the health of women during pregnancy, childbirth and the postnatal period.
Each stage should be a positive experience, ensuring women and their babies reach their full potential
for health and well-being.
Objective:

The present study aims to examine the association between women’s decision-making autonomy and
utilization of delivery services among the currently married women of urban India.

Methodology:
Descriptive statistics were carried out to understand the distribution of the samples by the key predictor,
covariates, and outcome variables. Bivariate distribution was presented to assess the prevalence of
delivery services (institutional delivery and PNC within 24 hours) by the independent variables, and
the differences were later tested by Pearson’s chi-square statistic. Relative Risk and its 95% CI were
computed for utilization of delivery services in respect of women’s autonomy and other independent
study variables.

Results:
From our study we found that about 87% of women in the low autonomy group and 89% in the medium
and high autonomy group each went for institutional delivery while the PNC care was utilized by only
71% women in the low autonomy, 78% in medium autonomy and 79% in high autonomy groups. The
relationship between the decision-making autonomy and Institutional delivery was found to be insignificant.

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