Robotics and Reproductive Surgery

Estes, Stephanie J.; Waldman, Ian; Gargiulo, Antonio R.

doi:10.1055/s-0037-1602594

Cited by 4 publications

(2 citation statements)

References 193 publications

(172 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Robotic surgery, a combination of both AI and minimally invasive surgery, used in various surgical fields has demonstrated superiority in complex gynecological diseases 28 . Uterine leiomyomas, adenomyosis, endometriosis, adnexal masses, tubal reanastomosis, and fertility preservation techniques can all benefit from robotic surgery 29 . Some robotics can even reduce vibrations to improve accuracy 2 .…”

Section: Artificial Intelligence In Gynecological Surgerymentioning

confidence: 99%

Artificial Intelligence in Clinical and Surgical Gynecology

Polat,

Arslan

2024

İstanbul Gelişim Üniversitesi Sağlık Bilimleri Dergisi

View full text Add to dashboard Cite

Clinicians have increasingly been using artificial intelligence (AI) to make decisions and to increase their knowledge in various clinical and surgical gynecological areas. A vast amount of clinical, medical, and biological patient data is processed in fast computer networks using complex algorithms to create mathematical modeling. The development of these mathematical models gives hope of a promising future with their contribution to overcoming the difficulties encountered in the diagnosis, individualization of treatment plans and improving patient outcomes. Virtual AI in clinical gynecology uses pattern recognition to aid diagnosis, plan treatment, and predict outcomes in gynecological malignancies, assisted reproductive techniques, and urogynecology. In gynecological surgery, physical AI combines augmented reality in operations in the form of computer-aided or robotic platforms. However, AI is yet to be fully incorporated into modern medical practice to improve patient outcomes in clinical gynecology.

show abstract

Section: Artificial Intelligence In Gynecological Surgerymentioning

confidence: 99%

Artificial Intelligence in Clinical and Surgical Gynecology

Polat,

Arslan

2024

İstanbul Gelişim Üniversitesi Sağlık Bilimleri Dergisi

View full text Add to dashboard Cite

show abstract

“…Robotic technology applied to laparoscopy has been introduced into clinical practice and has enhanced the armamentarium of the reproductive specialist. Uterine leiomyomas, adenomyosis, endometriosis, adnexal masses, sterilization reversal and fertility preservation techniques can all benefit from robotic surgery (Estes et al 2017). However, there are still little-randomized trials, and most studies published are observational or retrospective studies.…”

Section: Overview Of the Ai In Reproductive Medicinementioning

confidence: 99%

Artificial intelligence in reproductive medicine

et al. 2019

View full text Add to dashboard Cite

Artificial intelligence (AI) has experienced rapid growth over the past few years, moving from the experimental to the implementation phase in various fields, including medicine. Advances in learning algorithms and theories, the availability of large datasets and improvements in computing power have contributed to breakthroughs in current AI applications. Machine learning (ML), a subset of AI, allows computers to detect patterns from large complex datasets automatically and uses these patterns to make predictions. AI is proving to be increasingly applicable to healthcare, and multiple machine learning techniques have been used to improve the performance of assisted reproductive technology (ART). Despite various challenges, the integration of AI and reproductive medicine is bound to give an essential direction to medical development in the future. In this review, we discuss the basic aspects of AI and machine learning, and we address the applications, potential limitations and challenges of AI. We also highlight the prospects and future directions in the context of reproductive medicine.

show abstract

Surgical simulation supplements reproductive endocrinology and infertility fellowship training

et al. 2020

View full text Add to dashboard Cite

Objective: To assess if a surgical boot camp improves laparoscopic skill among reproduction endocrinology and infertility (REI) fellows and increases fellow desire to incorporate surgical skills into practice and to examine whether fellowship in vitro fertilization (IVF) volume correlates with surgical efficiency. Design: Prospective evaluation. Setting: Simulation Center. Patient(s): Forty REI fellows. Intervention(s): Fellows were timed before and after training in laparoscopic suturing and knot tying and while using virtual simulators. Fellows were surveyed before boot camp on prior experience with IVF and reproductive surgery, and immediately and 1 month after boot camp on their desire to incorporate surgical skills into practice. Main Outcome Measure(s): Efficiency of laparoscopic suturing and knot tying before and after boot camp; likelihood and persistence of incorporating surgical skills into practice immediately and 1 month after boot camp; and correlation between fellowship IVF volume and fellow surgical efficiency. Result(s): Fellows experienced significant improvement in laparoscopic suturing (44 sec), intracorporeal knot tying (82 sec), and extracorporeal knot tying (71 sec). Fellows reported being more likely to incorporate operative hysteroscopy (89%), operative laparoscopy (87%), and laparoscopic suturing (84%) into practice immediately following boot camp with no difference 1 month later. Fifty-four percent of fellows reported being more likely to perform robotic surgery after the boot camp, increasing to 70% 1 month later. There were weak correlations between IVF case volume and efficiency in laparoscopic suturing or hysteroscopic polypectomy (Spearman correlation coefficients,-0.14 and-0.03). Conclusion(s): An intensive surgical boot camp enhances surgical skill among REI fellows.

show abstract

Robotics and Reproductive Surgery

Cited by 4 publications

References 193 publications

Artificial Intelligence in Clinical and Surgical Gynecology

Artificial Intelligence in Clinical and Surgical Gynecology

Artificial intelligence in reproductive medicine

Surgical simulation supplements reproductive endocrinology and infertility fellowship training

Contact Info

Product

Resources

About