AIMC Topic: Polycystic Ovary Syndrome

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Automated high precision PCOS detection through a segment anything model on super resolution ultrasound ovary images.

Scientific reports
PCOS (Poly-Cystic Ovary Syndrome) is a multifaceted disorder that often affects the ovarian morphology of women of their reproductive age, resulting in the development of numerous cysts on the ovaries. Ultrasound imaging typically diagnoses PCOS, whi...

Advanced holographic convolutional dense networks and Tangent runner optimization for enhanced polycystic ovarian disease classification.

Scientific reports
Polycystic Ovarian Disease (PCOD) is among the most prevalent endocrine disorders complicating the health of innumerable women worldwide due to lack of diagnosis and appropriate management. The diagnosis of PCOD, along with proper classification with...

Advancement in early diagnosis of polycystic ovary syndrome: biomarker-driven innovative diagnostic sensor.

Mikrochimica acta
Polycystic ovary syndrome (PCOS) is a heterogeneous multifactorial endocrine disorder that affects one in five women around the globe. The pathology suggests a strong polygenic and epigenetic correlation, along with hormonal and metabolic dysfunction...

Construction and evaluation of machine learning-based prediction model for live birth following fresh embryo transfer in IVF/ICSI patients with polycystic ovary syndrome.

Journal of ovarian research
OBJECTIVE: To investigate the determinants affecting live birth outcomes in fresh embryo transfer among polycystic ovary syndrome (PCOS) patients using various machine learning (ML) algorithms and to construct predictive models, offering novel insigh...

A diagnostic model for polycystic ovary syndrome based on machine learning.

Scientific reports
Diagnosis of polycystic ovary syndrome remains a challenge. In this study, we propose constructing a diagnostic model of polycystic ovary syndrome by combining anti-Müllerian hormone with steroid hormones and oestrogens, with the aim of providing mor...

Identification of crucial genes for polycystic ovary syndrome and atherosclerosis through comprehensive bioinformatics analysis and machine learning.

International journal of gynaecology and obstetrics: the official organ of the International Federation of Gynaecology and Obstetrics
OBJECTIVE: To identify potential biomarkers in patients with polycystic ovary syndrome (PCOS) and atherosclerosis, and to explore the common pathologic mechanisms between these two diseases in response to the increased risk of cardiovascular diseases...

Optimized Machine Learning for the Early Detection of Polycystic Ovary Syndrome in Women.

Sensors (Basel, Switzerland)
Polycystic ovary syndrome (PCOS) is a medical condition that impacts millions of women worldwide; however, due to a lack of public awareness, as well as the expensive testing involved in the identification of PCOS, 70% of cases go undiagnosed. Theref...

Enhancing repeatability of follicle counting with deep learning reconstruction high-resolution MRI in PCOS patients.

Scientific reports
Follicle count, a pivotal metric in the adjunct diagnosis of polycystic ovary syndrome (PCOS), is often underestimated when assessed via transvaginal ultrasonography compared to MRI. Nevertheless, the repeatability of follicle counting using traditio...

Screening of serum biomarkers in patients with PCOS through lipid omics and ensemble machine learning.

PloS one
Polycystic ovary syndrome (PCOS) is a primary endocrine disorder affecting premenopausal women involving metabolic dysregulation. We aimed to screen serum biomarkers in PCOS patients using untargeted lipidomics and ensemble machine learning. Serum fr...

Development of machine learning models for diagnostic biomarker identification and immune cell infiltration analysis in PCOS.

Journal of ovarian research
BACKGROUND: Polycystic ovary syndrome (PCOS) is a common endocrine disorder affecting women of reproductive age. It is characterized by symptoms such as hyperandrogenemia, oligo or anovulation and polycystic ovarian, significantly impacting quality o...