Current developments in artificial intelligence from obstetrics and gynecology to urogynecology

Bridging gaps in artificial intelligence adoption for maternal-fetal and obstetric care: Unveiling transformative capabilities and challenges

PURPOSE

This review aims to comprehensively explore the application of Artificial Intelligence (AI) to an area that has not been traditionally explored in depth: the continuum of maternal-fetal health. In doing so, the intent was to examine this physiologically continuous spectrum of mother and child health, as well as to highlight potential pitfalls, and suggest solutions for the same.

METHOD

A systematic search identified studies employing AI techniques for prediction, diagnosis, and decision support employing various modalities like imaging, electrophysiological signals and electronic health records in the domain of obstetrics and fetal health. In the selected articles then, AI applications in fetal morphology, gestational age assessment, congenital defect detection, fetal monitoring, placental analysis, and maternal physiological monitoring were critically examined both from the perspective of the domain and artificial intelligence.

RESULT

AI-driven solutions demonstrate promising capabilities in medical diagnostics and risk prediction, offering automation, improved accuracy, and the potential for personalized medicine. However, challenges regarding data availability, algorithmic transparency, and ethical considerations must be overcome to ensure responsible and effective clinical implementation. These challenges must be urgently addressed to ensure a domain as critical to public health as obstetrics and fetal health, is able to fully benefit from the gigantic strides made in the field of artificial intelligence.

CONCLUSION

Open access to relevant datasets is crucial for equitable progress in this critical public health domain. Integrating responsible and explainable AI, while addressing ethical considerations, is essential to maximize the public health benefits of AI-driven solutions in maternal-fetal care.

Get the Artificial Intelligence (AI) Edge in Obstetrics and Gynaecology

Artificial intelligence (AI) is on the fast track so far as the growth is concerned, from experimental to implementation in field of medicine. AI should be used ethically and intelligently. Large data base availability, advances in algorithm-theories, computing improvements has led to breakthrough in AI applications in current medicine. Machine learning (ML), which is subset of AI, allows computers to detect patterns through larger data base automatically, that can be used to make predictions. Is it paradigm shift? In the field of Obstetrics and Gynaecology, AI is used in reproductive medicine for diagnosis, treatment with fertility outcome, cancer treatment, USG-MRI images diagnosis, foetal echocardiography, cardiotocography (CTG), preterm labour prediction and urogynaecology. ChatGPT can be helpful in medical writing but there is always a challenge with respect to accuracy and reliability. AI can be used in research and experiments, there by strengthening evidence-based clinical practice. More research is ongoing on personalized diagnosis, treatment and remote medical expert team opinion. It does not replace the medical advice given by the clinician but that should not deter clinician by exploring more uses of AI. Despite various challenges and limitations, integration of AI in medical field is bound to progress in correct direction for better future.

The Role of Artificial Intelligence in Urogynecology: Current Applications and Future Prospects

Artificial intelligence (AI) is the new medical hot topic, being applied mainly in specialties with a strong imaging component. In the domain of gynecology, AI has been tested and shown vast potential in several areas with promising results, with an emphasis on oncology. However, fewer studies have been made focusing on urogynecology, a branch of gynecology known for using multiple imaging exams (IEs) and tests in the management of women's pelvic floor health. This review aims to illustrate the current state of AI in urogynecology, namely with the use of machine learning (ML) and deep learning (DL) in diagnostics and as imaging tools, discuss possible future prospects for AI in this field, and go over its limitations that challenge its safe implementation.

ChatGPT in Urogynecology Research: Novel or Not?

IMPORTANCE

ChatGPT (Chat Generative Pre-trained Transformer) is an artificial intelligence (AI) chatbot that provides human-like responses to text prompts. Little is known regarding ChatGPT's ability to identify original research ideas in urogynecology.

OBJECTIVE

Our objective was to evaluate the accuracy of ChatGPT in generating novel systematic review (SR) and research ideas in urogynecology.

STUDY DESIGN

In this cross-sectional study, we asked ChatGPT to generate 10 novel SR ideas that have not yet been published for each of the following 5 topics: (1) urogynecology, (2) tension-free vaginal tape slings, (3) pessaries for pelvic organ prolapse, (4) beta-3 agonist use for overactive bladder, and (5) sexual function with genitourinary syndrome of menopause. Research idea novelty was assessed by cross-referencing PubMed and Scopus to determine if any prior publications existed.

RESULTS

ChatGPT proposed 50 total SR ideas, including 10 for each prompt. Overall, ChatGPT showed 54% overall accuracy in developing novel SR ideas. Nonnovel SR ideas had a median of 19 (interquartile range, 8-35) published SRs on the suggested topic. When stratified by prompt type, 50% of general and 40-70% of specific urogynecology proposed SR ideas were found to be novel. There were no publications of any type identified for 7 of the 50 suggested ideas.

CONCLUSIONS

ChatGPT may be helpful for identifying novel research ideas in urogynecology, but its accuracy is limited. It is essential for those using ChatGPT to review existing literature to ensure originality and credibility. As AI transforms health care, we encourage all urogynecologists to familiarize themselves with popular AI platforms.

Revolutionizing Women's Health: A Comprehensive Review of Artificial Intelligence Advancements in Gynecology

Artificial intelligence has yielded remarkably promising results in several medical fields, namely those with a strong imaging component. Gynecology relies heavily on imaging since it offers useful visual data on the female reproductive system, leading to a deeper understanding of pathophysiological concepts. The applicability of artificial intelligence technologies has not been as noticeable in gynecologic imaging as in other medical fields so far. However, due to growing interest in this area, some studies have been performed with exciting results. From urogynecology to oncology, artificial intelligence algorithms, particularly machine learning and deep learning, have shown huge potential to revolutionize the overall healthcare experience for women's reproductive health. In this review, we aim to establish the current status of AI in gynecology, the upcoming developments in this area, and discuss the challenges facing its clinical implementation, namely the technological and ethical concerns for technology development, implementation, and accountability.

The role of artificial intelligence in the future of urogynecology

Artificial intelligence (AI) in medicine is a rapidly growing field aimed at using machine learning models to improve health outcomes and patient experiences. Many new platforms have become accessible and therefore it seems inevitable that we consider how to implement them in our day-to-day practice. Currently, the specialty of urogynecology faces new challenges as the population grows, life expectancy increases, and quality of life expectation is much improved. As AI has a lot of potential to promote the discipline of urogynecology, we aim to explore its abilities and possible use in the future. Challenges and risks are associated with using AI, and a responsible use of such resources is required.