AI Medical Compendium Journal:
Reproductive sciences (Thousand Oaks, Calif.)

Showing 1 to 7 of 7 articles

Unveiling the Role of Artificial Intelligence (AI) in Polycystic Ovary Syndrome (PCOS) Diagnosis: A Comprehensive Review.

Reproductive sciences (Thousand Oaks, Calif.)
Polycystic Ovary Syndrome (PCOS) is one of the most widespread endocrine and metabolic disorders affecting women of reproductive age. Major symptoms include hyperandrogenism, polycystic ovary, irregular menstruation cycle, excessive hair growth, etc....

The Promise and Challenges of AI Integration in Ovarian Cancer Screenings.

Reproductive sciences (Thousand Oaks, Calif.)
PURPOSE: Ovarian cancer is oftendiagnosed late due to vague symptoms, leading to poor survival rate. Improved screening tests could mitigate this issue. This narrative review examines the potential and challenges of integrating artificial intelligenc...

Automation in ART: Paving the Way for the Future of Infertility Treatment.

Reproductive sciences (Thousand Oaks, Calif.)
In vitro fertilisation (IVF) is estimated to account for the birth of more than nine million babies worldwide, perhaps making it one of the most intriguing as well as commoditised and industrialised modern medical interventions. Nevertheless, most IV...

Candidate Circulating Biomarkers of Spontaneous Miscarriage After IVF-ET Identified via Coupling Machine Learning and Serum Lipidomics Profiling.

Reproductive sciences (Thousand Oaks, Calif.)
Spontaneous miscarriage is a common pregnancy complication. Multiple etiologies have been proposed such as genetic aberrations, endocrinology disorder, and immunologic derangement; however, the relevance of circulating lipidomes to the specific condi...

Human Oocyte Morphology and Outcomes of Infertility Treatment: a Systematic Review.

Reproductive sciences (Thousand Oaks, Calif.)
Oocyte morphology assessment is easy to implement in any laboratory with possible quality grading prior to fertilization. At present, comprehensive oocyte morphology scoring is not performed as a routine procedure. However, it may augment chances for...

Deep Learning of Markov Model-Based Machines for Determination of Better Treatment Option Decisions for Infertile Women.

Reproductive sciences (Thousand Oaks, Calif.)
In this technical article, we are proposing ideas, that we have been developing on how machine learning and deep learning techniques can potentially assist obstetricians/gynecologists in better clinical decision-making, using infertile women in their...

Machine Learning for Predicting Stillbirth: A Systematic Review.

Reproductive sciences (Thousand Oaks, Calif.)
Stillbirth is a major global issue, with over 5 million cases each year. The multifactorial nature of stillbirth makes it difficult to predict. Artificial intelligence (AI) and machine learning (ML) have the potential to enhance clinical decision-mak...