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Jan 2026
Kaur KirandeepCorresponding author
Background Female infertility has always been an issue and social stigma in India and it’s not only the matter of physical health of the female but also related to psychological health and the social status of the women. The diagnosis of this problem criterion requires medical symptoms for the condition, including clinical and metabolic parameters. The application of AI-driven algorithms into medical science is responsible for the specific phrase Medical Artificial Intelligence (MAI) which has introduced a transformative swing in female reproductive health, qualifying higher diagnostic accuracy, reproducibility, and efficiency in addressing complex conditions such as infertility and hormonal disorders. From Ovarian stimulation to Artificial Intelligence in Assisted Reproductive Technology, there have been significant advancements in the incorporation of machine learning and IoT in the medical Labs. AI algorithms are expected to bring about a more calculated, computed, and standardized approach to the infertility problem today females are facing. Aim This review aims to establish connection between female infertility problems with AI and discusses how an effort can be made to resolve such sensitive health issue, keeping in view the recent and past contribution of emerging AI technologies in health sciences. The AI trained models are based on either supervised learning algorithms of unsupervised learning algorithms. Basically the input to the medical trained AI models is the set of instances referred to as medical dataset which can be categorized, clustered or correlated as per requirements. Each instance is further described by the values of a set of attributes like diagnosis, treatment, laboratory tests data, prescription drugs etc. These medical dataset can be further represented in the form of matrix and later can be used to aid learning methods that is supervised or unsupervised learning methods to train AI medical models. That is why the term MAI is being used in this review paper. Methods Used Studies were explored across IEEE Xplore, PubMed, ResearchGate, SpringerLink and npj Digital Medicine for papers published. Following the database probing, identical articles were pull out and the lasting titles and abstracts were inspected for suitability. Studies were incorporated if they portrayed the role of Artificial Intelligence for female reproductive health or infertility problems in reproductive age. Result Following data was extracted from 12 selected articles. These studies were eventually chosen for complete estimation. Conclusion AI has proved to be an incomparable assistance tool in providing specialist approach in the reproductive health issues in females. But there is need to describe ways to develop a framework of wearable technology in the form of sensor to predict correct ovulation period.
Jul 2021 DOI 10.14302/issn.2576-2818.jfb-20-3559
Adetona AdesojiCorresponding author
Nigeria
Background Male Infertility accounts for 30-40% of all cases of infertility and its evaluation requires a good history, thorough physical examination, and several investigations to include testicular biopsy which might be used to further categorize infertile males for proper management and prognostication. This study aims to determine the predominant histopathological patterns of testicular biopsies in infertile males and to compare the findings with previous studies. Methods A retrospective cross-sectional study of 225 selected cases of testicular biopsies reviewed for the evaluation of male infertility in the Pathology department, of a tertiary hospital, Southwest, Nigeria, between 1987 and 2012. Relevant clinical and histopathological information was extracted from the departmental records. All histologic cases were reviewed, and a classification based on histological patterns of spermatogenesis was utilized to group the cases into normal findings, hypo spermatogenesis, maturation arrest, Sertoli cell-only syndrome, peritubular hyalinization/ tubular fibrosis and mixed patterns. The data obtained were analysed using descriptive and inferential statistics at a 5% level of significance. Results Among the 225 cases reviewed with a mean age of 37.7 years (SD - 8.61), 82.7% had primary infertility of which 92.9% were azoospermic, while 7.1% had oligospermia. The histological patterns included 34.2% of Hypospermatogenesis, 32% of Peritubular hyalinization/ tubular fibrosis, 14.2% had maturation arrest and Sertoli cell-only syndrome was found in 6.7% of cases, only 0.9% had normal histologic pattern while the mixed histologic pattern was seen in 12% of cases. Conclusion The commonest morphological pattern was Hypospermatogenesis, which is similar to some of the previous local and international studies. A high percentage of peritubular fibrosis was noted with few tubules containing scanty late spermatids or spermatozoa when proper sampling and evaluation were made. Multiple patterns within a biopsy were seen with careful review, especially in non-obstructive azoospermic cases. This is significant in male infertility patient management in our environment because it suggests greater chances of successful sperm extraction for Assisted Reproduction Technique in such patients.
Mar 2021 DOI 10.14302/issn.2574-4372.jesr-20-3593
Hernández Víctor Manuel VargasCorresponding author
Female Health Clinic, Mexico
Background Women play an important role in the work setting. This leads them to put off their motherhood, sometimes preventing them from getting pregnant. Delaying pregnancy face women with low ovarian response, such as in Premature Ovarian Insufficiency (POI) or Ovarian Aging (OA). There is no current treatment, although there is evidence of improving ovarian function by inyecting mesenchymal stem cells (MSC). Materials and Methods Prospective, observational study of 17 women who attended Pronatal Clinic from 2019 to 2020. Each patient was registered in Assisted Reproductive Treatment (ART) and was enrolled in ovarian treatment with an autologous adipose tissue Mesenchymal Stem Cell (AD-MSCs) protocol. Three groups were assembled: 1) Control: AMH >1.2 ng/mL, without AD-MSCs, 2) POI/OA: female infertility due to POI/OA with AMH <1.2 ng/mL and 3) Amenorrhea: female infertility due to POI/OA with amenorrhea and AMH <1.2 ng/mL. Variables: Age, weight, height, serum AMH, endometrial thickness, follicular size and number on day 2 and 11 of the menstrual cycle, oocyte number, number of blastocysts and pregnancy rate. Results Between month 2 and 5, after AD-MSCs inyection, POI/OA group showed an increase in follicle number (2 to 9) and size (13.5 to 15.5 mm) on day 11 of the menstrual cycle, which resulted in a higher number of MII oocytes (2.6 to 4.2), and an increase in number of blastocysts (0 to 3) and endometrial thickness (8.6 to 9.4). Regarding the Amenorrhea group, a reboot in menstrual cycle was observed, although no further development of blastocyst was found. Conclusion The AD-MSCs inyection directly in the ovary allowed an increase in number of blastocysts and improved pregnancy rates in POI/OA patients.
Sep 2018 DOI 10.14302/issn.2377-2549.jndc-18-2315
Jana SnehasisCorresponding author
Trivedi Science Research Laboratory Pvt. Ltd.,Bhopal, India
Selenium is an essential micronutrient required for healthy metabolism, as well as prevention, and treatment of selenium deficiency diseases. The experiment aimed to evaluate the influence of the Trivedi Effect®-Consciousness Energy Healing Treatment on the physicochemical and thermal properties of selenium using modern analytical techniques. The selenium sample was divided into two parts, one part of the test sample was called the control sample, while the second part of the test sample received the Biofield Treatment remotely by a renowned Biofield Energy Healer, Gopal Nayak, and was called the treated sample. The particle size values were significantly decreased by 37.69% (d10), 14.36% (d50), 4.31% (d90), and 11.58% D(43), hence, the specific surface area was significantly increased by 33.64% in the treated sample compared to the control sample. The PXRD peak intensities and crystallite sizes were significantly altered ranging from 5.23% to 100% and 75% to 111.7%, respectively; whereas 7.81% significantly decreased the average crystallite size in the treated sample than the control sample. The latent heat of fusion of the treated sample was significantly increased by 12.37% compared with the control sample.The results suggested that the Trivedi Effect® might generate a new polymorphic form of selenium which would offer better solubility, bioavailability and be thermally more stable compared with the control sample. The Biofield Treated selenium would be more useful to design novel nutraceutical/pharmaceutical formulations and might offer an enhanced therapeutic response against cardiovascular disease, cancer, neuromuscular disorders, diabetes, stress, aging, male infertility, viral diseases, degenerative ailments, etc.