METHOD OF PREDICTING EFFECTIVENESS OF ASSISTED REPRODUCTIVE TECHNOLOGY PROGRAMS BASED ON NEURAL NETWORKS Russian patent published in 2023 - IPC A61B8/00 G01N33/68 G01N33/48 

FIELD: medicine; obstetrics and gynecology.

SUBSTANCE: invention can be used to predict the effectiveness of assisted reproductive technology programs in women with infertility of various origins in medical decision support systems. At the first stage of the implementation of the protocol for in vitro fertilization (IVF) programs, medical history data, an objective examination and the results of clinical, laboratory and instrumental studies are collected, and the option of the protocol for stimulating superovulation, the starting and total doses of follicle-stimulating hormone and the need to include drugs containing luteinizing hormone are also selected. Then, using all the data obtained: the doctor’s work experience, diagnosis according to ICD N10, age, height and weight of the patient, IVF attempt number, presence of human immunodeficiency virus (HIV) in women and men, presence of chronic hepatitis B or C in women and men, the presence of human papillomavirus (HPV) in a woman, a history of arterial hypertension and/or diabetes mellitus types 1, 2, hemoglobin level in the blood, the count of red blood cells, leukocytes, lymphocytes, platelets in the blood formula, fasting glucose concentration, level of alanine aminotransferase (ALT), aspartate aminotransferase (AST), creatinine, cholesterol, bilirubin, concentration of follicle-stimulating hormone (FSH) and anti-Mullerian hormone (AMH) in the patient’s venous blood, the count of antral follicles on the right and left before stimulation, type of stimulation protocol, starting and the total dose of FSH, the presence of luteinizing hormone (LH) in the stimulation protocol as predictors, using a predictive mathematical model of the first stage, the probability of obtaining 5 or less oocytes, from 6 to 19 oocytes, or 20 or more oocytes suitable for fertilization is calculated. Further, when such oocytes are obtained as a result of puncture, at the second stage of the IVF protocol, the qualitative and quantitative characteristics of the sperm intended for fertilization are determined. The proposed options for fertilization and embryo cultivation are selected. Then, using all the data obtained, namely: the type of stimulation protocol performed, the actual starting and total doses of FSH, the presence of LH in the stimulation protocol, the actual number of days of stimulation, the use of a gonadotropin-releasing hormone (GnRH) agonist or human chorionic gonadotropin as a trigger (hCG), the concentration of estradiol (E2) and progesterone in the blood before puncture, the number of follicles and complexes before puncture of the ovaries according to ultrasound (ultrasound), the number of oocytes obtained as a result of puncture, of which the number of mature oocytes at metaphase stage 2 (M-2 ), number of immature oocytes of the metaphase 1 (M-1) stage, number of immature oocytes of the "Germinal Vesular" (GV) stage and number of degenerative oocytes, source of sperm and method of obtaining sperm, use of cryo-freezing of sperm, number of sperm after treatment, percentage of motile sperm category A+B, percentage of morphologically normal sperm, use of intracytoplasmic sperm injection (ICSI) during fertilization, types of media used for fertilization, cleavage and culture, number of 2PN zygotes obtained, in addition to the first stage data, as predictors, and using a predictive mathematical model of the second stage, the probability of obtaining embryos suitable for transfer into the uterine cavity or cryopreservation in an amount of 1 to 2, 3 or more, or the probability of a negative result, i.e. 0 embryos on the fifth day after fertilization is calculated. When such embryos are obtained, at the third stage of the IVF protocol, the thickness of the endometrium is determined using ultrasound. A decision is made to use a GnRH agonist. Then, using all the data obtained, namely: the number of embryos suitable for transfer, the use of embryo cryopreservation, the thickness of the endometrium before transfer, the presence of complications during the embryo transfer procedure, and the use of a GnRH agonist, in addition to the data from the first and second stages, as predictors, using a prognostic mathematical model of the third stage, the probability of pregnancy is calculated as a percentage. Each of the three predictive mathematical models is implemented in the form of an artificial neural network pre-trained on a prepared data set with an architecture in the form of a multilayer fully connected Rumelhart perceptron.

EFFECT: invention provides accurate prediction of the effectiveness of the implementation of each stage of the IVF protocol, through the use of artificial neural networks as a mathematical apparatus, which, in turn, makes it possible to effectively take into account a large number of heterogeneous predictors and the possibility of making changes to the protocol in order to increase overall efficiency.

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