Artificial intelligence: A rapid case for advancement in the personalization of Gynaecology/Obstetric and Mental Health care

Abstract

To evaluate and holistically treat the mental health sequelae and potential psychiatric comorbidities associated with obstetric and gynaecological conditions, it is important to optimize patient care, ensure efficient use of limited resources and improve health-economic models. Artificial intelligence applications could assist in achieving the above. The World Health Organization and global healthcare systems have already recognized the use of artificial intelligence technologies to address ‘system gaps’ and automate some of the more cumbersome tasks to optimize clinical services and reduce health inequalities. Currently, both mental health and obstetric and gynaecological services independently use artificial intelligence applications. Thus, suitable solutions are shared between mental health and obstetric and gynaecological clinical practices, independent of one another. Although, to address complexities with some patients who may have often interchanging sequelae with mental health and obstetric and gynaecological illnesses, ‘holistically’ developed artificial intelligence applications could be useful. Therefore, we present a rapid review to understand the currently available artificial intelligence applications and research into multi-morbid conditions, including clinical trial-based validations. Most artificial intelligence applications are intrinsically data-driven tools, and their validation in healthcare can be challenging as they require large-scale clinical trials. Furthermore, most artificial intelligence applications use rate-limiting mock data sets, which restrict their applicability to a clinical population. Some researchers may fail to recognize the randomness in the data generating processes in clinical care from a statistical perspective with a potentially minimal representation of a population, limiting their applicability within a real-world setting. However, novel, innovative trial designs could pave the way to generate better data sets that are generalizable to the entire global population. A collaboration between artificial intelligence and statistical models could be developed and deployed with algorithmic and domain interpretability to achieve this. In addition, acquiring big data sets is vital to ensure these artificial intelligence applications provide the highest accuracy within a real-world setting, especially when used as part of a clinical diagnosis or treatment.

Postpartum From the Preconceptional Period Period Innovative Developments

“…Gebelik döneminde kadınların tanı, tedavi, bakım olanaklarını geliştirmek, gebelikte görülebilecek riskli durumları erken dönemde saptamak, gebelikte görülen hastalıkların yönetimini sağlamak, gebelerin yaşam kalitelerini yükseltmek, gebelikle ilişkili komplikasyonlardan anne ile yenidoğan mortalite ve morbiditesini azaltmak, fetüsün gelişimi, elektronik izleme ve genetik tarama gibi birçok uygulama alanında inovatif yaklaşımlar geliştirilmiştir (22). Bu inovatif yaklaşımlar arasında; gebelik öncesi ovülasyon süreci takibi, gebelikte tarama, uzaktan gebelik takibi, farmakoloji, fetüs gelişimi, elektronik izleme, postpartum süreçte komplikasyonların erken teşhisi, doğum sonrası eğitim süreçlerinin yürütülmesine yönelik ürünler yer almaktadır (13,23).…”

A Theoretical Exploration of Artificial Intelligence’s Impact on Feto-Maternal Health from Conception to Delivery

“…In the context of healthcare, AI has been increasingly applied to various medical domains, including radiology, cardiology, surgery, oncology and obstetrics. [17][18][19] AI algorithms can process and analyze large volumes of data, making it possible to identify subtle patterns and deviations that might go unnoticed through traditional medical tests. 17 In recent years, AI has found a significant role in the field of feto-maternal health.…”

Artificial intelligence and social media on academic performance and mental well-being: Student perceptions of positive impact in the age of smart learning

“…Our study pivots to accentuate student perceptions of the positive influence of social media on academic performance, countering the common narrative of its detrimental psychological impact [ 17 ]. Prior research has explored the addictive tendencies of social media and the corresponding threats to mental well-being, such as cyberbullying and online harassment [ [18] , [19] , [20] ]. Accordingly, a nuanced understanding of the impacts of these technologies on academic performance and mental health is warranted.…”