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• Artificial intelligence-based prediction model for body fat percentage (BFP). • Artificial intelligence-based BFP prediction model for men and women. • BFP prediction model with electrocardiography signal. • Low cost BFP prediction model with practical use. • BFP prediction model with high accuracy. Body fat percentage (BFP) is a frequently used parameter in the assessment of body composition. The body is made up of fat, muscle and lean body tissues. Excess fat tissue in the body causes obesity. Obesity is a treatable disease that decreases the quality of life. Obesity can trigger ailments such as psychological disorders, cardiovascular diseases and respiratory and digestive problems. Dual energy X-ray absorptiometry gold standard method is laborious, costly and time consuming. For this reason, more practical methods are needed. The aim of this study is to develop BFP prediction models with gender-based electrocardiography (ECG) signal and machine learning methods. In the study, 25 features were extracted from seven different QRS bands and filtered and unfiltered ECG signals. In addition, age, height and weight were used as features. Spearman feature selection algorithm was used to increase the performance. The BFP prediction models developed have performance values of R = 0.94 for men and R = 0.93 for women and R = 0.91 for all individuals. Feature selection algorithm helped increase performance. According to the results, it is thought that ECG based BFP prediction models can be used in practice. [ABSTRACT FROM AUTHOR]

: Objective:To report the birth of a healthy female infant from a father with nonmosaic Klinefelter syndrome (KS) and document the experience of men with KS undergoing assisted conception.: Design:Retrospective.: Setting:Private IVF center.: Patient(s):Twelve couples with male factor infertility due to Klinefelter syndrome undergoing assisted reproduction treatment.: Intervention(s):Controlled ovarian hyperstimulation, testicular sperm extraction, intracytoplasmic sperm injection (ICSI), round spermatid injection (ROSI), and preimplantation genetic diagnosis.: Main outcome measure(s):Testicular sperm retrieval rate, fertilization rate, and pregnancy outcome.: Result(s):There was a sufficient amount of motile sperm for injection into mature oocytes in 6 of the 11 testicular biopsies (54.5%). Fertilization rates for ICSI and ROSI cases were 54.2% and 41.6%, respectively. The pregnancy rate per ET was 27.2%. None of the ROSI cases resulted in pregnancy. Two patients had spontaneous abortions at 8 and 18 weeks of gestation, respectively. Only one patient delivered a healthy female baby after 36 weeks of an uneventful pregnancy.: Conclusion(s):Men with KS can benefit from assisted reproductive technologies, and the testicular sperm retrieval rate among them is promising. Although sex chromosome aberrations among the embryos from men with KS are not common, couples can be offered preimplantation genetic diagnosis before ET. [Copyright &y& Elsevier]

: ObjectiveTo report a case of cervical heterotopic pregnancy after IVF-ET treatment.: DesignCase report.: SettingPrivate IVF center.: Patient(s)A woman who had undergone controlled ovarian hyperstimulation and intracytoplasmic sperm injection–ET for primary male factor infertility.: Intervention(s)Resection of cervical heterotopic pregnancy by hysteroscopy.: Main outcome measure(s)Successful treatment of heterotopic cervical pregnancy.: Result(s)A successful pregnancy resulting in a term baby.: Conclusion(s)Hysteroscopic resection can be used to treat a cervical heterotopic pregnancy. [Copyright &y& Elsevier]

Objective: To compare the outcome of day 2 and day 3 embryo transfers in women demonstrating poor ovarian response. Design: Prospective randomized clinical trial. Setting: Private assisted reproductive technology center. Patient(s): Two hundred eighty-one women demonstrating poor ovarian response to controlled ovarian hyperstimulation. Intervention(s): Women who were poor responders were randomly allocated to day 2 or day 3 embryo transfer following oocyte retrieval. Main Outcome Measure(s): Implantation rates and pregnancy rates per oocyte retrieval and embryo transfer. Result(s): The clinical pregnancy rates per oocyte retrieval (37.2% vs. 21.4%, respectively; P<.05) and per embryo transfer (38.9% vs. 24.1%, respectively; P<.05) were significantly higher in the day 2 embryo transfer group compared with day 3. On the other hand, implantation rates were not different between groups (23.9% vs. 17.2%, respectively; P=.08). Conclusion(s): Our results demonstrated that transfering embryos on day 2 could provide an alternative to the management of poor responder patients. [Copyright &y& Elsevier]