Digital Mobile Application development for prediction of Pre-eclampsia among pregnant women .

Hi, I'm Diwash Oli from Nepal currently on my third year of my Bachelor of Network Security Degree at Norther Sydney Institute of TAFE NSW, Meadowbank Campus. 

One of the subjects in the first semester of this year, Major Group Project, requires us students to develop a real-life working project by the end of the semester. As the subject suggests, our class is divided into groups and each group has to come up with a project that is effective, easily implementable and sensible in the real world. 

I fall under the second group and we are five members in the group working together to accomplish a project. In the beginning, we had to find a suitable project that met the requirements of the subjects. We came across various possible projects that could be effective and usable for everyone. However, as we had to work on one project, our group came up with the idea of developing a mobile application that can predict Pre-Eclampsia among pregnant women.

Pre-Eclampsia is a serious , and a possible life-threatening disease that arise among pregnant women. The problem is most likely to begin between the 20th and 25th week of the pregnancy, in other words, during the second half phase of pregnancy period. Pregnant women with high blood pressure, protein in urine which is effectively called as Proteinuria , etc. are the common factors involved in causing the disease. Swelling of hands/feet, regular headaches, change in vision, abdominal pain etc. should be closely monitored as these have high probability of occurrence in women with Pre-Eclampsia.

The disease is so dangerous that it directly impacts the patient's liver, kidney, eyes, and heart. And to mention the worst, this can also cause severe brain damage and stroke.

Knowing the severity of the disease , the popularity among pregnant women and recent impact caused by COVID-19, our group recognised the importance of developing a mobile application that could help predict the disease once given the data about blood pressure, urine analysis, fetal ultrasound of a pregnant women. The app will be designed to cross-reference the data with the database containing all the related information and even conduct discussions with medical professional of needed before finally giving out the predicted result .

Myself and my group mate are involved in the programming part of the project. We have decided to use Python as the base programming language for the application development and use the Kivy and KivyMD framework to develop the app and make it cross-platform functional. 

At this stage our group has presented the project charter and is now working on the Literature Review of the project. Our PM  has allocated certain areas of research among all the among members, and I am currently performing research on a decision tree model for the application along with further research on various Kivy library features.