%0 Journal Article
%T Utilization of Artificial Intelligence for Diagnosis and Management of Urinary Incontinence in Women Residing in Areas with Low Resources: An Overview
%A Amad Qureshi
%A Aanchal Mathur
%A Jonia Alshiek
%A S. Abbas Shobeiri
%A Qi Wei
%J Open Journal of Obstetrics and Gynecology
%P 403-418
%@ 2160-8806
%D 2021
%I Scientific Research Publishing
%R 10.4236/ojog.2021.114040
%X Urinary incontinence (UI) is a distressing condition involving
involuntary</span><span style=\"font-family:Verdana;\"> loss of urine from the body. Urinary incontinence
can negatively impact a person</span><span style=\"font-family:Verdana;\">¡¯</span><span style=\"font-family:Verdana;\">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</span><span style=\"font-family:Verdana;\">/management</span><span style=\"font-family:Verdana;\"> options.
There are different diagnostic and </span><span style=\"font-family:Verdana;\">management</span><span style=\"font-family:Verdana;\"> protocols for UI; however, utilizing artificially intelligent systems is
not standard care. This paper overviews</span><span style=\"font-family:&quot;\"> </span><span style=\"font-family:Verdana;\">the use of artificial intelligence in women</span><span style=\"font-family:Verdana;\">¡¯</span><span style=\"font-family:Verdana;\">s health and as a means of
cost-effectively diagnosing patients,</span><span style=\"font-family:&quot;\"> </span><span style=\"font-family:Verdana;\">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 </span><span style=\"font-family:Verdana;\">(ANNs) </span><span style=\"font-family:Verdana;\">and convolution</span><span style=\"font-family:Verdana;\">al</span><span style=\"font-family:Verdana;\"> neural networks</span><span style=\"font-family:Verdana;\"> (CNNs)</span><span style=\"font-family:&quot;\"><span style=\"font-family:Verdana;\">, served
to be an effective method in diagnosing patients and providing an avenue for
personalized treatment for improved patient outcomes. A simple artificial intel</span><span style=\"font-family:Verdana;\">ligence (AI) model utilizing Multilayer Perceptron
(MLP) Networks was</span><span style=\"font-family:Verdana;\"> proposed to diagnose and </span></span><span style=\"font-family:Verdana;\">manage</span><span style=\"font-family:Verdana;\"> urinary incontinence.
%K Urinary Incontinence
%K Artificial Intelligence
%K Women¡¯s Health
%K Underdeveloped Regions
%U http://www.scirp.org/journal/PaperInformation.aspx?PaperID=108656