Telemedicine and Artificial Intelligence in the Management of Endometriosis: Future Forecast Considering Current Progress

Geburtsh Frauenheilk 2023; 83: 116 –117 DOI 10.1055/a-1950-6634 ISSN 0016-5751 © 2022. The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial-License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commercial purposes, or adapted, remixed, transformed or built upon. (https://creativecommons.org/licenses/by-nc-nd/4.0/). Georg Thieme Verlag KG, Rüdigerstraße 14, 70 469 Stuttgart, Germany Correspondence Assoc. Prof. MD. MSc. Cihan Kaya Dept. Ob/Gyn Acibadem Bakirkoy Hospital Halit Ziya Usakligil Cd 1 34 140 Bakırköy/Istanbul, Turkey [email protected] Dear Editor, In recent decades, communication and computer-based tech- nologies have successfully been adapted to healthcare manage- ment [1]. Besides, these technologies have been widely imple- mented into daily practice, especially for managing patients suffering from chronic diseases such as endometriosis during the COVID-19 pandemic [2]. Due to pandemic restrictions, most endometriosis patients who seek a remedy for pain relief or infertility could not attend hospitals. This situation caused a potential risk for endometriosis patients considering acute complications such as intestinal ob- struction, rectal or urinary bleeding, cyst rupture, and severe abdominal pain [3]. Apart from urgent hospital admissions, endometriosis manage- ment requires experience and dedication both in medical and surgical management. However, it is not always easy to attain an experienced endometriosis center or specialists for patients with severe endometriosis. Therefore patients need to look for appro- priate healthcare professionals or clinics in di fferent cities or countries. All practical options provided by technology should be consid- ered in endometriosis management regarding the necessities mentioned above. Recently, many qualified centers have encour- aged healthcare providers to use Telemedicine (TM) appointments to maintain health care and support patients with chronic dis- eases. TM is accessible simply via a computer, tablet, or smart- phone, which only requires a proper internet connection and a video transmission platform [4]. TM o ffers various advantages, such as remote communication with physicians and laboratory or imaging findings interpretation. Furthermore, TM could contribute to an appropriate patient fol- low-up and decision-making process [4]. From the endometriosis aspect, TM could allow physicians to communicate with patients who su ffer from pain and are anxious about the side e ffects or Kaya C et al. Telemedicine and Artificial ... Geburtsh Frauenheilk 2023; 83: 116 –117 | © 2022. The Author(s).116 GebFra Science | Letter to the Editor Article published online: 2022-11-29 effectiveness of the previously recommended medical treatments [3]. In addition to adapting communication technologies to the healthcare system, computer-based advancements are also used in various specialties. Artificial intelligence (AI) systems have re- cently been investigated for diagnostic purposes in cardiology, ophthalmology, psychiatry, radiology, and nuclear medicine [5]. The majority of AI studies have concentrated on improving medi- cal image quality, noise reduction, quality assurance, triage, com- puter-based diagnosis, and radiogenomics as an emerging area of research [6]. AI system-based developments substantially mimic human neuronal connections via various processors, including artificial neurons like human beings [7]. The AI systems require machine learning technology, big data analysis processes, and advanced ro- botic systems. Besides, many graphic processing units are needed to process massive data following segmentation and regeneration steps. As a plain explanation, the AI processes enable analyzing and interpreting radiological or surgical images by matching previously registered proven data [8]. Although AI in surgery practice is still in its infancy period, the progress of technology is promising. Regarding the diagnosis of endometriosis, the patient ’s history, gynecological examination, and imaging methods have a crucial role. However, experience in ultrasonography or MRI interpreta- tion is required in the diagnosis of endometriotic lesions. For that purpose, AI-based software could interpret an MRI or sonographic image [5, 9]. Moreover, aside from the diagnosis of endometriosis, it could be possible to utilize AI in the surgical management of endo- metriosis. The studies regarding the prototypes of artificial surgery programs that mimic surgeons ’ movements in predetermined cases have already been reported [10]. The AI-based surgical software includes regenerated video content obtained from essential frames after extraction from thousands of hours of surgery videos that correspond to key events of the procedures (i.e., dissection and coagulation, restora- tion of the pelvic anatomy, reaction to bleeding, resection of the affected organ, and suturing) performed by experts [1, 10]. The idea behind including only essential frames of the surgery is related to the fact that each surgery has relevant or redundant short movements, even performed by experienced hands. The AI aims to choose those frames with as much relevant data as possi- ble. The system then combines the appropriate frames and regenerates them to obtain an accurate surgical flow. This AI-based advancement could create many opportunities for both surgeons and patients. Besides, AI may allow physicians to compare their movements with the data acquired from expert surgeons [1, 10]. AI-based platforms may also be adapted to robotic surgery systems that convert the entire process to an automated surgery. Moreover, AI-based surgeries could enhance the intra/postoperative outcomes by combining with the pre- operative imaging data [1, 5, 10]. In conclusion, over the next few years, it is evident that the development of communication technology and AI will provide a mind-blowing advancement. Healthcare providers should be familiar with the current progress in technology since inevitable outcomes are on the line. Contributors' Statement CK: Conceptualization, Data curation, Project administration, Writing – review and editing. TU: Writing – review and editing. EO: Writing – review and editing. Conflict of Interest The authors declare that they have no conflict of interest.

[1] Teixeira J. One Hundred Years of Evolution in Surgery: From Asepsis to Artificial Intelligence. Surg Clin North Am 2020; 100: xv –xvi. doi:10.101 6/j.suc.2020.01.001 [2] Leonardi M, Horne AW, Vincent K et al. Self-management strategies to consider to combat endometriosis symptoms during the COVID-19 pan- demic. Hum Reprod Open 2020; 1: hoaa028. doi:10.1093/hropen/hoaa0 28 [3] Yalç ın Bahat P, Kaya C, Selçuki NFT et al. The COVID-19 pandemic and patients with endometriosis: A survey-based study conducted in Turkey. Int J Gynaecol Obstet 2020; 151: 249 –252. doi:10.1002/ijgo.13339 [4] Mann DM, Chen J, Chunara R et al. COVID-19 transforms health care through telemedicine: Evidence from the field. J Am Med Inform Assoc 2020; 27: 1132 –1135. doi:10.1093/jamia/ocaa072 [5] Yu KH, Beam AL, Kohane IS. Artificial intelligence in healthcare. Nat Biomed Eng 2018; 2: 719 –731. doi:10.1038/s41551-018-0305-z [6] Weichert J, Welp A, Scharf JL et al. The Use of Artificial Intelligence in Automation in the Fields of Gynaecology and Obstetrics – an Assessment of the State of Play. Geburtshilfe Frauenheilkd 2021; 81: 1203 –1216. doi:10.1055/a-1522-3029 [7] Uemura M, Tomikawa M, Miao T et al. Feasibility of an AI-Based Measure of the Hand Motions of Expert and Novice Surgeons. Comput Math

Med 2018; 2018: 9873273. doi:10.1155/2018/9873273 [8] Alonso-Silverio GA, Pérez-Escamirosa F, Bruno-Sanchez R et al. Develop- ment of a Laparoscopic Box Trainer Based on Open Source Hardware and Artificial Intelligence for Objective Assessment of Surgical Psychomotor Skills. Surg Innov 2018; 25: 380 –388. doi:10.1177/1553350618777045 [9] Thalluri AL, Knox S, Nguyen T. MRI findings in deep infiltrating endome- triosis: A pictorial essay. J Med Imaging Radiat Oncol 2017; 61: 767 –773. doi:10.1111/1754-9485.12680 [10] Loukas C, Varytimidis C, Rapantzikos K et al. Keyframe extraction from laparoscopic videos based on visual saliency detection. Comput Methods Programs Biomed 2018; 165: 13 –23. doi:10.1016/j.cmpb.2018.07.004 Kaya C et al. Telemedicine and Artificial ... Geburtsh Frauenheilk 2023; 83: 116 –117 | © 2022. The Author(s). 117