Intelligent assisted living in pregnancy

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Date

2022-01

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BRAC University

Abstract

Pregnancy period has always been the most sensitive and tenacious phase for the mothers to go through. Despite living in this modern world, it is still difficult to fight with the distress and complications of pregnancy, and that the rate of unfortunate miscarriages and stunting are still seen to be rising in this era. The huge advancement of technology, however, has stood up as a shield to protect and prevent these misfortunes from taking place, at a very early stage, by taking some of its useful measures. Artificial Intelligence is playing a vital role in this case and is able to serve aid in this regard. With the help of these techniques, we have decided and attempted to come up with a proposal of a system that is smart enough to assist like a doctor. Taking account of all the minor and major symptoms and difficulties that a woman faces during her pregnancy period, our system will provide an effective outcome based on the information provided by that mother and will encourage the person to take necessary actions. It is often seen that the health issues that a woman faces during her pregnancy period is considered lightly since a visit to the doctor can prove costly. Considering these issues, our proposed application will work its best to instantly impart the solutions for all the common difficulties that a mother may go through during this tough time. This smart proposed application, therefore, aims to conduct operations based on diagnosing the complications the pregnant women face with the data of the symptoms they are showing while also predicting possible miscarriage or severe health complications.

Description

Cataloged from PDF version of thesis.
Includes bibliographical references (pages 47-49).
This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2022.

Keywords

Data mining, Pregnancy, Miscarriage, Complications, Prediction, Decision tree, Linear regression analysis, Chatbot

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