Table 3.
Reported clinical characteristics included as features in the AI models.
| Author | Patient clinical characteristics | Embryo morphology features |
|---|---|---|
| Uyar et al. (2009) | Woman’s age*, Infertility factor, Treatment protocol, FSH dosage, Peak Estradiol level | Early cleavage morphology, early cleavage time, transfer day, number of cells, nucleus characteristics, fragmentation rate, equality of blastomeres |
| Blank et al. (2019) | Female age*, Male age, AMH Level, TSH Level, Gravidity, Abortus, Therapeutic Abortus, Parity, Indication: (Tubal Causes, Endometriosis, Ovarian Causes, Genetic Causes (female), Genetic Causes (male), Uterine Causes, Male Factor, Non-medical Causes, Cervical Causes, Repeated Miscarriage, Hypothalamic Dysfunction, Immunologic Causes, Oncological Causes, Unexplained), Ovarian Stimulation Protocol, Down-regulation Protocol, Days of Stimulation, Number of Attempt, Sperm Source, Sperm Collection Method, Sperm Volume, Sperm Concentration, Sperm Motility Rate, Number of Oocytes, Number of fertilized Cells, Fertilization Method, Number of Egg Cells | Day 2 (cell stage, fragmentation, cytoplasma, cell-specific size, cell size, nuclei, MNB, vacuoles), Day 3 (cell stage, fragmentation, cytoplasma, cell-specific size, cell size, vacuoles), Day 4 (cell stages, vacuoles), Day 5 (cell stage, ICM, TE) |
| Uyar et al. (2015) | Female age*, Gravidity, Infertility factor, Treatment protocol, Utilized sperm, Duration of stimulation (days), FSH, Peak E2 level, Endometrium thickness, Early cleavage inspection time, Early cleavage morphology | Number of cells, nucleus characteristics, fragmentation rate, equality of blastomeres, appearance of cytoplasm, thickness of zona pellucida, transfer day (Days 2–3) |
| Hariton et al. (2021) | Trigger day, Estradiol, BMI, Age at start of treatment, Total no. of follicles, Estradiol/follicles, Maximum follicle size, Eggs retrieved, Mature eggs retrieved, Total no. of eggs fertilized | Total usable blastocysts |
| Raef et al. (2020) | Female age*, male age*, BMI, Family relation of couples, Family relation in parents of couples, Smoking, Type of infertility, Infertility duration, Contraception duration, Infertility in family, gravida, parity, abortion, ectopic pregnancy, living children, dead children, Comorbidity diseases, Anemia, Thyroid disease, Prolactin hormone disorders, Drug usage, Amenorrhea, Dysmenorrhea, Period status, Hirsutism, Galactorrhea, Gynecological surgery, Oocyte donation, AFC, Endometrium thickness, Three-line (regular/normal) endometrium, Uterus depth, Size of follicles, Tubal factor, Pelvic factor, Cervical factor, Ovulatory factor, PCOS, Uterine factor, Endometriosis, Endometrial factor, Vaginitis, RIF, recurrent pregnancy loss, Thrombophilia disorders, Immunologic disorders, Male factor, Male genital surgery, Varicocele, TESE, PESE, Fresh/freeze sperm, Sperm count, Normal morph, Immotile, FSH, LH, Estradiol vitD3 Levels, FSH/HMG dosage, GnRH, antagonists Dosage, GnRH agonists dosage, Duration of stimulation (days), Estradiol dosage, No. estradiol days, Number of retrieved oocytes, Number of metaphase II quality oocytes, Number of metaphase I quality oocytes, Number of germinal vesicle quality oocytes, Number of degenerated quality oocytes, Quality of injected metaphase II oocytes | Number of 2PN (pronuclear), number of developed embryos, quality of developed embryos, quality of vitelline space, ET (embryo transfer), ET day, number of transferred embryos, number of blastomeres, quality and stages of transferred embryos, experience of ET |
| Sawada et al. (2021) | Age*, Method of fertilization, Type of culture media | Mode of embryo transfer |
AI, artificial intelligence; RIF, repeat implant failure; PESE, percutaneous epididymal sperm extraction; TESE, testicular sperm extraction; AFC, antral follicle count; AMH, anti-Müllerian hormone; TSH, thyroid-stimulating hormone; E2, estradiol; vitD3, vitamin D3; ET, embryo transfer; 2PN, 2 pronuclei; ICM, inner cell mass; TE, trophectoderm; MNB, multinucleated blastomeres. (*) indicates the feature with most influence on the performance of the AI model.