AIMC Topic: Polycystic Ovary Syndrome

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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...

Development of a machine learning model to classify polycystic ovarian syndrome.

Technology and health care : official journal of the European Society for Engineering and Medicine
BackgroundOne of the main causes of infertility among women nowadays is Polycystic Ovarian Syndrome, or PCOS. A decision support strategy for supporting medical specialists through PCOS monitoring is presented in the suggested work. A feature selecti...

Comparative evaluation of ChatGPT-4, ChatGPT-3.5 and Google Gemini on PCOS assessment and management based on recommendations from the 2023 guideline.

Endocrine
CONTEXT: Artificial intelligence (AI) is increasingly utilized in healthcare, with models like ChatGPT and Google Gemini gaining global popularity. Polycystic ovary syndrome (PCOS) is a prevalent condition that requires both lifestyle modifications a...

Exploring acetylation-related gene markers in polycystic ovary syndrome: insights into pathogenesis and diagnostic potential using machine learning.

Gynecological endocrinology : the official journal of the International Society of Gynecological Endocrinology
OBJECTIVE: Polycystic ovary syndrome (PCOS) is a prevalent cause of menstrual irregularities and infertility in women, impacting quality of life. Despite advancements, current understanding of PCOS pathogenesis and treatment remains limited. This stu...

Identification of key biomarkers for predicting atherosclerosis progression in polycystic ovary syndrome via bioinformatics analysis and machine learning.

Computers in biology and medicine
OBJECTIVE: Polycystic ovary syndrome (PCOS) is one of the most significant cardiovascular risk factors, playing vital roles in various cardiovascular diseases such as atherosclerosis (AS). This study attempted to explore key biomarkers for predicting...

F-Net: Follicles Net an efficient tool for the diagnosis of polycystic ovarian syndrome using deep learning techniques.

PloS one
The study's primary objectives encompass the following: (i) To implement the object detection of ovarian follicles using you only look once (YOLO)v8 and subsequently segment the identified follicles using a hybrid fuzzy c-means-based active contour t...

Predicting Unfavorable Pregnancy Outcomes in Polycystic Ovary Syndrome (PCOS) Patients Using Machine Learning Algorithms.

Medicina (Kaunas, Lithuania)
: Polycystic ovary syndrome (PCOS) is a complex disorder that can negatively impact the obstetrical outcomes. The aim of this study was to determine the predictive performance of four machine learning (ML)-based algorithms for the prediction of adver...

Predicting Metformin Efficacy in Improving Insulin Sensitivity Among Women With Polycystic Ovary Syndrome and Insulin Resistance: A Machine Learning Study.

Endocrine practice : official journal of the American College of Endocrinology and the American Association of Clinical Endocrinologists
OBJECTIVE: Metformin is clinically effective in treating polycystic ovary syndrome (PCOS) with insulin resistance (IR), while its efficacy varies among individuals. This study aims to develop a machine learning model to predict the efficacy of metfor...