ISSN No. (Print): 0975-1718 ISSN No. (Online): 2249-3247 Fuzzy Computerized Profile Prediction of Luteinizing Hormone Nutan Verma 1 , Vivek Raich 2 and Sharad Gangele 1 1 R.K.D.F University Bhopal (Madhya Pradesh), India 2 Govt. Holkar Science College Indore (Madhya Pradesh), India 1 R.K.D.F University Bhopal (Madhya Pradesh), India (Corresponding author: Nutan Verma) (Received 06 February 2018, Accepted 24 April, 2018) (Published by Research Trend, Website: www.researchtrend.net) ABSTRACT: The aim of the study is to predict the hormonal profile of Luteinizing Hormone throughout the female menstrual cycle. The present research acknowledged just for healthy, adult and non-pregnant female. The proposed new technique used fuzzy logic as tool to deal with uncertainty and estimate LH profile under various circumstances. Fuzzification appertain on conventional reference degree of LH, utilized trapezoidal membership (μ L , μ N and μ H ) and if-then rule to evaluate LH as low, normal and high. Keywords: Infertility, Luteinizing Hormone (LH), μ L , μ N and μ H . NOMENCLATURE: μ L is low fuzzy membership function, μ N is normal fuzzy membership function, μ H is high fuzzy membership function. I. INTRODUCTION Reproduction is re-produce or produce again, is a continuous process. Reproduction is essential for the survival of organism. This study is corresponding to human. Females having capability to give birth to human, because of the female menstrual cycle. Fertility defines reproduction and relationship between fertility and infertility, infertility is inversely propositional to fertility. Now a day’s infertility becomes a global issue among fertile aged couples. According to bulletin of The World Health Organization (WHO) (http://www.who.int/ bulletin/volumes/88/12/10- 011210/en/), infertility affects up to 15% of reproductive-aged couples worldwide. The development of reproductive technologies has enabled better reproductive efficiency and treatment for infertility. Infertility defined, as 1 year of attempted conception without success, is one of the most common health disorders relating young adults. Clinical evaluation of infertility specified that if a pregnancy has not occurred after 1 year of regular unprotected intercourse, because by that time 85% of couples attempting conception will have been successful [4]. Infertility is an issue, caused by both male and female. This study concerns with female infertility. There are many factors affects fertility like environmental, social, biological, psychological etc. Female fertility diagnosis begins with the diagnosis of female menstrual cycle. Typical female menstrual cycle is of 28 days of an adult female. During the cycle various hormones like Follicle Stimulating Hormone (FSH), Luteinizing Hormone (LH), Prolactin (PRL), Progesterone and Estrogen takes part under various circumstances. A Fuzzy Logic System for fertility prediction corresponding to the Basal Body Temperature (BBT) technique based on FAM, help females to predict their fertility based on automatic BBT charting and online monitoring concepts, effectively [10]. In this experiment, author endeavored to counsel answer for regarding the issue with medical expert’s that they don’t have general electronic LH estimate through the female menstrual cycle. Mathematical conversion of a real-life problem with uncertainty is a complex issue. Fuzzy Logic establish itself as a one of the best tool to resolve uncertainty and facility with the lingual conversion of the same also. That is why, fuzzy logic used as a tool to execute the methodology. The proposed work introduces a novel fuzzy equation model to deliver final model to figure rate of fertility (female fertility) which give more appropriate infertility analysis and will help in infertility management. Better infertility management is accomplished by giving precision to the medical expert’s prognosis with respect to LH status all through the female menstrual cycle. Conventional hormonal analysis approach is, if current test value between its standard reference range is ponder as normal. If current test value below its lower limit is reckon as low and if greater then upper limit is considered as high. This fuzzification methodology is applied on standard normal reference range of LH, independently for all three phases of female menstrual cycle. International Journal of Theoretical & Applied Sciences, 10(1): 234-238(2018)