Predicting Changes in Core Muscles During Female Sexual Dysfunction: A Comprehensive Analysis Using Machine and Deep Learning

Deraya University

Status: Completed

Conditions: Female Sexual Dysfunction

Treatments: Other: no intervention

Study type: Observational

Funder types: Other

Identifiers

NCT05833685

P.REC/ 6/2023

Details and patient eligibility

About

The purpose of this study is to Predicting changes in core muscles during female sexual dysfunction by A Comprehensive Analysis Using Machine and Deep Learning Female sexual dysfunction (FSD) is a common condition that affects womenof all ages. It is characterized by a range of symptoms, including decreased libido, difficulty achieving orgasm, and pain during intercourse. One potential cause of FSD is muscular weakness or changes in the core muscles. These muscles play an important role in sexual function, and changes in their strength or activation patterns can lead to FSD. Additionally, the development of a machine learning model for this purpose could pave the way for future studies exploring the use of artificial intelligence in the diagnosis and treatment of other musculoskeletal disorder and female health issues.

Enrollment: 100 patients

Sex: Female

Ages: 30 to 40 years old

Volunteers: No Healthy Volunteers

Inclusion criteria

• a number of parities ≤ three
• normal vaginal deliveries

Exclusion criteria

• History of a recto-vaginal or vesico-vaginal fistula, undiagnosed uterine bleeding urinary tract infection,
• diabetes,
• intrauterine device
• sexual disorder

Trial design

100 participants in 2 patient groups

Female sexual dysfunction group

Treatment:

Other: no intervention

Normal females

Treatment:

Other: no intervention