TITLE:
Utilization of Artificial Intelligence for Diagnosis and Management of Urinary Incontinence in Women Residing in Areas with Low Resources: An Overview
AUTHORS:
Amad Qureshi, Aanchal Mathur, Jonia Alshiek, S. Abbas Shobeiri, Qi Wei
KEYWORDS:
Urinary Incontinence, Artificial Intelligence, Women’s Health, Underdeveloped Regions
JOURNAL NAME:
Open Journal of Obstetrics and Gynecology,
Vol.11 No.4,
April
25,
2021
ABSTRACT: Urinary incontinence (UI) is a distressing condition involving
involuntary loss of urine from the body. Urinary incontinence
can negatively impact a person’s overall
quality of life and lead them into stages of embarrassment and depression. It
is an underrepresented and undertreated condition prevalent in women,
especially in low socioeconomic regions where women may not be able to express
their concerns due to unawareness of diagnosis and treatment/management options.
There are different diagnostic and management protocols for UI; however, utilizing artificially intelligent systems is
not standard care. This paper overviews the use of artificial intelligence in women’s health and as a means of
cost-effectively diagnosing patients, and as an avenue for providing low-cost treatments to women that suffer
from urinary incontinence in low-resource communities. Studies found that these
systems, mainly utilizing artificial neural networks (ANNs) and convolutional neural networks (CNNs), served
to be an effective method in diagnosing patients and providing an avenue for
personalized treatment for improved patient outcomes. A simple artificial intelligence (AI) model utilizing Multilayer Perceptron
(MLP) Networks was proposed to diagnose and manage urinary incontinence.