Abstract
Now a days, hormonal disorder causing Polycystic Ovary Syndrome (PCOS) is been observed in most of the women of reproductive age. PCOS causes enlarged ovaries with small cysts on the outer edges. Women with PCOS may have irregularity in menstrual periods or excess male hormone (androgen) levels. The ovaries may develop numerous small collections of follicles (cysts) and fail to regularly release eggs. Symptoms of PCOS include irregular periods, excess androgen, polycystic ovaries, abnormal Body Mass Index, disturbed levels of hormones (Luteinizing Hormone, Follicle-stimulating Hormone, Dehydroepiandros- terone), poor insulin resistance. There is a need to design and develop an optimized system to analyze the sonogram in correlation with the physical symptoms for detection of PCOS at early stage which may result in proper treatment and reduced health loss. This article presents work-in-progress of our proposed research on Intelligent System to detect PCOS. The performance analysis of various Machine learning algorithms like Artificial Neural Network, K- nearest Neighbor and Linear Regression to detect PCOS is presented. Whereas, optimized Genetic Clustering for optimization of classification results is proposed. Basic Genetic Algorithm (GA) and other hybrid GA’s will be used for comparing the optimal results. The classification results are optimized with 89% accuracy
Highlights
Disorders of the woman reproductive system can occur as a result of disorder in one of the many various reproductive organs: the ovaries, uterus, cervix, the vagina, or the cause behind occurring of these diseases is hormonal changes inside the body, hormonal imbalance, stress, irregular living patterns, etc
The classification results are optimized with 89% accuracy
These attributes are the symptoms related to Polycystic ovary syndrome (PCOS) such as physical symptoms(age, height, weight, irregular periods, hirsutism, acne), and blood test results; (LH(Luteinizing hormone), follicle stimulating hormone (FSH)(Follicle-stimulating hormone), androgen level, DHEAS, fasting insulin, fasting blood sugar) and clinical test
Summary
Disorders of the woman reproductive system can occur as a result of disorder in one of the many various reproductive organs: the ovaries, uterus, cervix, the vagina, or the cause behind occurring of these diseases is hormonal changes inside the body, hormonal imbalance, stress, irregular living patterns, etc. Polycystic ovary syndrome (PCOS) is the most common endocrine disease in women at reproductive age group. Women with PCOS produce an high amount of androgen than normal [1] This hormone imbalance causes abnormality in menstrual cycle and leads to infertility. Genetic Clustering for Polycystic Ovary Syndrome detection in women of reproductive age (male hormone), causing issues with ovulation. “Coagulation parameters predictive of polycystic ovary syndrome”[13], which proposed there were 181 patients having PCOS (selected according to Rotterdam criteria) and 301 controls were selected. “A Classification of Polycystic Ovary Syndrome Based on Follicle Detection of Ultrasound Images”[14], which proposed 80 images, consisting of 60 normal ovary images and 20 images of PCOS ovary. To improve classification performance of large scale of data, Genetic Algorithm (GA) was proposed. Two objective functions give the initial partitions in first stage and other two give optimal clustering centers
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