Artificial intelligence can benefit reproductive technologies by increasing the treatment options and pregnancy outcomes.
FREMONT, CA: Artificial intelligence (AI) is the technology of making machines do things that will need intelligence if performed by humans. AI has developed quickly, and its applications have pervaded regular lives, including automated vehicles, facial recognition, and intelligent voice assistance. AI is also utilized in healthcare in various fields like radiology, oncology, and cardiology, benefitting from its applications.
Artificial intelligence is not a new concept in the research world of assisted reproductive technologies (ART). It was introduced with the creation of an algorithm whose objective was to predict the result of IVF. Later, ore technologies used various types of algorithms in different ways, including oocyte, embryo selection, and sperm cell.
The researchers trained an AI algorithm that can accurately identify the high and low-quality embryos. The AI algorithms improved the performance objectively because the embryologists responsible for assessing the embryo quality utilizing morphological analysis are subjective evaluations that involved manual grading of the human embryo. Even though the algorithm cannot predict pregnancy rates, the exact information that it can offer about the embryo quality is an important variable that might enhance the couple’s chance of conceiving.
The potential of artificial intelligence in clinical ART will offer immense benefits and ethical complexities. If it is accepted for clinical application, AI can separate the high-quality embryos from the ones that are chromosomally abnormal. It will save healthcare professionals time and effort by processing and interpreting more data with better depth and precision. Such technologies will enhance the efficiency of ART and pregnancy results, treatment options, and even care for patients dealing with infertility. It can also reduce healthcare expenses by decreasing the usage of unnecessary testing or treatment.
The utilization of AI in ART moves forward from research to the clinic because every stakeholder, including the general public, scientists, decision-makers, and clinicians, is anticipating and reflecting on the challenges that can arise. Few of the challenges can be familiar to the ones raised by AI in other healthcare sectors.