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.

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

100 patients were distributed randomly into two groups. Female sexual dysfunction group and another group is normal females. Two group will be measure Transverses muscle ratio, Multifidus muscle ratio ,diaphragm excursion and force of contraction of pelvic floor muscles by ultrasound imaging, VLQ and FSFI questionnaires for female sexual function VLQ and FSFI questionnaires for female sexual dysfunction and normal females. Patients will be examined by radiologist with medical ultrasound imaging