A Review of Soft Computing Used in Assisted Reproductive Techniques (ART)

Nearly eighty million people all over the world are suffering from infertility related problems. This problem has aggravated due to several reasons like change in lifestyle, infections, genetic issues, postponed childbearing, etc. Assisted reproductive technology (ART) is the technology used to achieve pregnancy using several types of medical procedures. ART involves three basic procedures viz., intrauterine insemination (IUI), in-vitro fertilization (IVF), intra cytoplasmic sperm injection (ICSI) and are generally carried out in stages. The overall success rate of the treatment is very less , which makes a negative impact on the patient’s psychology seeking ART treatment. This psychological change also affects the practitioners to deal with patients. The success rate of the fertility treatment is based on the experience and techniques applied by every individual practitioner. The current challenges that the ART practitioners are facing is to improve the treatment results. It is therefore necessary to use computing techniques and machine learning techniques to assist the medical practitioner to predict or get better results for the treatment administered. This paper reviews soft computing techniques applied in the field of ART on the data available at ART clinics and sperm banks. This review throws light on various soft computing techniques used in the field of ART and will also help to study several issues for further improvement .