Knowledge of Cervical Cancer among Women of Childbearing Age: A Qualitative Study of Ngwo Community In Udi LGA Of Enugu

Chikasie Ruth Ikpeama , FAVOUR UROKO

Background: This study is to ascertain the level of awareness of cervical cancer among women of child bearing age in Udi Local Government of Enugu State. It is also determine the factors that contribute to lack of knowledge of cervical cancer among women of childbearing age in Udi Local Government of Enugu State. Cancer of the cervix otherwise known as Cervical Cancer is a disease of public health importance affecting a significant number of women globally. Sub-Saharan Africa has the highest rates of cervical cancer in the world, largely attributed to low cervical cancer screening coverage.

Aim: The purpose of this study was to assess cervical cancer awareness among women of reproductive age in Udi Local Government. An exploratory research design was used in this study.

Methods: The study took place in Udi Local Government Area of Enugu state, Nigeria. The study used an in-depth interview (IDI) guide that was carefully created based on the major topics that needed to be covered data gathering.

Findings: Findings from the study show their understanding translate into screening uptake, ignorance, and having multiple sexual partners. The study found that the level of knowledge of cervical cancer among women of child bearing age in Enugu State is low even though the study participants identified being aware that it is a disease that affects women.

Conclusion: The findings of this study suggest that there is a need to improve the level of knowledge of cervical cancer among women of child bearing age in Enugu State. This can be done through public awareness campaigns and by providing women with access to accurate information about cervical cancer and its prevention. Healthcare professionals also play an important role in educating women about cervical cancer and encouraging them to get screened regularly.

A DECISION MODEL BASED ON ARTIFICIAL INTELLIGENCE FOR DISEASE PREDICTION AND PATIENT TREATMENT PROCESS PLANNING

Serkan Derici

Purpose: The aim of this study is to determine which patients are at risk of lung cancer with a sample of 1000 people living in China and a data set consisting of 20 variables. In this direction, it is aimed to take preventive measures for individuals at risk of developing lung cancer, to protect human health, and to contribute to the effective and efficient use of resources. In this way, the model developed in the planning of preventive and therapeutic activities of professionals working in the health sector will be exemplary as a decision model.

Methodology: A linear regression model was developed and applied to predict individuals at high risk of developing lung cancer using machine learning on the Microsoft Azure Machine Learning Studio platform.

Findings: Lung cancer risk of the patients in the sample was predicted with the machine learning application. It was determined that these predictions made with machine learning gave an effective result and provided efficient policies. The developed model and application example is proposed as a modern, valid and artificial intelligence-based decision-making model for professionals.

Originality: There are few statistical analysis and machine learning applications for lung cancer prediction in the literature. In this paper, in addition to the prediction model, statistical analyses will be performed, preventive measures will be proposed, and the scope of the analyses will be made holistic by linking it to efficiency in resource utilization. As a result, this will enable professionals to make optimal decisions.

Asia Pacific Journal of Health Management

Knowledge of Cervical Cancer among Women of Childbearing Age: A Qualitative Study of Ngwo Community In Udi LGA Of Enugu

A DECISION MODEL BASED ON ARTIFICIAL INTELLIGENCE FOR DISEASE PREDICTION AND PATIENT TREATMENT PROCESS PLANNING