{"paper_id":"d4a287c8-5935-4751-bc64-d18e376a7292","body_text":"Telemedicine and Artificial Intelligence in the Management\nof Endometriosis: Future Forecast Considering Current Progress\nTelemedizin und künstliche Intelligenz bei der Behandlung\nvon Endometriose: Zukunftsprognose unter Berücksichtigung\nder aktuellen Fortschritte\nAuthors\nCihan Kaya1, Taner Usta 2, Engin Oral 3\nAffiliations\n1 Dept. Ob/Gyn, Acibadem Bakirkoy Hospital, Bak ırköy/\nIstanbul, Turkey\n2 Dept. Ob/Gyn, Acibadem Altunizade Hospital, Acibadem\nMehmet Ali Aydinlar University, Istanbul, Turkey\n3 Dept. Ob/Gyn, Faculty of Medicine, Bezmialem Vakif\nUniversity, Istanbul, Turkey\nKey words\nartifical intelligence, diagnosis, endometriosis, telemedicine\nSchlüsselwörter\nkünstliche Intelligenz, Diagnose, Endometriose, Telemedizin\npublished online 29.11.2022\nBibliography\nGeburtsh Frauenheilk 2023; 83: 116 –117\nDOI 10.1055/a-1950-6634\nISSN 0016-5751\n© 2022. The Author(s).\nThis is an open access article published by Thieme under the terms of the Creative\nCommons Attribution-NonDerivative-NonCommercial-License, permitting copying\nand reproduction so long as the original work is given appropriate credit. Contents\nmay not be used for commercial purposes, or adapted, remixed, transformed or built\nupon. (https://creativecommons.org/licenses/by-nc-nd/4.0/).\nGeorg Thieme Verlag KG, Rüdigerstraße 14,\n70 469 Stuttgart, Germany\nCorrespondence\nAssoc. Prof. MD. MSc. Cihan Kaya\nDept. Ob/Gyn\nAcibadem Bakirkoy Hospital\nHalit Ziya Usakligil Cd 1\n34 140 Bakırköy/Istanbul, Turkey\ndrcihankaya@gmail.com\nDear Editor,\nIn recent decades, communication and computer-based tech-\nnologies have successfully been adapted to healthcare manage-\nment [1]. Besides, these technologies have been widely imple-\nmented into daily practice, especially for managing patients\nsuffering from chronic diseases such as endometriosis during the\nCOVID-19 pandemic [2].\nDue to pandemic restrictions, most endometriosis patients\nwho seek a remedy for pain relief or infertility could not attend\nhospitals. This situation caused a potential risk for endometriosis\npatients considering acute complications such as intestinal ob-\nstruction, rectal or urinary bleeding, cyst rupture, and severe\nabdominal pain [3].\nApart from urgent hospital admissions, endometriosis manage-\nment requires experience and dedication both in medical and\nsurgical management. However, it is not always easy to attain an\nexperienced endometriosis center or specialists for patients with\nsevere endometriosis. Therefore patients need to look for appro-\npriate healthcare professionals or clinics in di fferent cities or\ncountries.\nAll practical options provided by technology should be consid-\nered in endometriosis management regarding the necessities\nmentioned above. Recently, many qualified centers have encour-\naged healthcare providers to use Telemedicine (TM) appointments\nto maintain health care and support patients with chronic dis-\neases. TM is accessible simply via a computer, tablet, or smart-\nphone, which only requires a proper internet connection and a\nvideo transmission platform [4].\nTM o ffers various advantages, such as remote communication\nwith physicians and laboratory or imaging findings interpretation.\nFurthermore, TM could contribute to an appropriate patient fol-\nlow-up and decision-making process [4]. From the endometriosis\naspect, TM could allow physicians to communicate with patients\nwho su ffer from pain and are anxious about the side e ffects or\nKaya C et al. Telemedicine and Artificial ... Geburtsh Frauenheilk 2023; 83: 116 –117 | © 2022. The Author(s).116\nGebFra Science | Letter to the Editor\nArticle published online: 2022-11-29\n\neffectiveness of the previously recommended medical treatments\n[3].\nIn addition to adapting communication technologies to the\nhealthcare system, computer-based advancements are also used\nin various specialties. Artificial intelligence (AI) systems have re-\ncently been investigated for diagnostic purposes in cardiology,\nophthalmology, psychiatry, radiology, and nuclear medicine [5].\nThe majority of AI studies have concentrated on improving medi-\ncal image quality, noise reduction, quality assurance, triage, com-\nputer-based diagnosis, and radiogenomics as an emerging area of\nresearch [6].\nAI system-based developments substantially mimic human\nneuronal connections via various processors, including artificial\nneurons like human beings [7]. The AI systems require machine\nlearning technology, big data analysis processes, and advanced ro-\nbotic systems. Besides, many graphic processing units are needed\nto process massive data following segmentation and regeneration\nsteps. As a plain explanation, the AI processes enable analyzing\nand interpreting radiological or surgical images by matching\npreviously registered proven data [8]. Although AI in surgery\npractice is still in its infancy period, the progress of technology is\npromising.\nRegarding the diagnosis of endometriosis, the patient ’s history,\ngynecological examination, and imaging methods have a crucial\nrole. However, experience in ultrasonography or MRI interpreta-\ntion is required in the diagnosis of endometriotic lesions. For that\npurpose, AI-based software could interpret an MRI or sonographic\nimage [5, 9].\nMoreover, aside from the diagnosis of endometriosis, it could\nbe possible to utilize AI in the surgical management of endo-\nmetriosis. The studies regarding the prototypes of artificial surgery\nprograms that mimic surgeons ’ movements in predetermined\ncases have already been reported [10].\nThe AI-based surgical software includes regenerated video\ncontent obtained from essential frames after extraction from\nthousands of hours of surgery videos that correspond to key\nevents of the procedures (i.e., dissection and coagulation, restora-\ntion of the pelvic anatomy, reaction to bleeding, resection of the\naffected organ, and suturing) performed by experts [1, 10].\nThe idea behind including only essential frames of the surgery\nis related to the fact that each surgery has relevant or redundant\nshort movements, even performed by experienced hands. The AI\naims to choose those frames with as much relevant data as possi-\nble. The system then combines the appropriate frames and\nregenerates them to obtain an accurate surgical flow.\nThis AI-based advancement could create many opportunities\nfor both surgeons and patients. Besides, AI may allow physicians\nto compare their movements with the data acquired from expert\nsurgeons [1, 10]. AI-based platforms may also be adapted to\nrobotic surgery systems that convert the entire process to an\nautomated surgery. Moreover, AI-based surgeries could enhance\nthe intra/postoperative outcomes by combining with the pre-\noperative imaging data [1, 5, 10].\nIn conclusion, over the next few years, it is evident that the\ndevelopment of communication technology and AI will provide a\nmind-blowing advancement. Healthcare providers should be\nfamiliar with the current progress in technology since inevitable\noutcomes are on the line.\nContributors' Statement\nCK: Conceptualization, Data curation, Project administration, Writing –\nreview and editing. TU: Writing – review and editing. EO: Writing –\nreview and editing.\nConflict of Interest\nThe authors declare that they have no conflict of interest.\nReferences\n[1] Teixeira J. One Hundred Years of Evolution in Surgery: From Asepsis to\nArtificial Intelligence. Surg Clin North Am 2020; 100: xv –xvi. doi:10.101\n6/j.suc.2020.01.001\n[2] Leonardi M, Horne AW, Vincent K et al. Self-management strategies to\nconsider to combat endometriosis symptoms during the COVID-19 pan-\ndemic. Hum Reprod Open 2020; 1: hoaa028. doi:10.1093/hropen/hoaa0\n28\n[3] Yalç ın Bahat P, Kaya C, Selçuki NFT et al. The COVID-19 pandemic and\npatients with endometriosis: A survey-based study conducted in Turkey.\nInt J Gynaecol Obstet 2020; 151: 249 –252. doi:10.1002/ijgo.13339\n[4] Mann DM, Chen J, Chunara R et al. COVID-19 transforms health care\nthrough telemedicine: Evidence from the field. J Am Med Inform Assoc\n2020; 27: 1132 –1135. doi:10.1093/jamia/ocaa072\n[5] Yu KH, Beam AL, Kohane IS. Artificial intelligence in healthcare. Nat\nBiomed Eng 2018; 2: 719 –731. doi:10.1038/s41551-018-0305-z\n[6] Weichert J, Welp A, Scharf JL et al. The Use of Artificial Intelligence in\nAutomation in the Fields of Gynaecology and Obstetrics – an Assessment\nof the State of Play. Geburtshilfe Frauenheilkd 2021; 81: 1203 –1216.\ndoi:10.1055/a-1522-3029\n[7] Uemura M, Tomikawa M, Miao T et al. Feasibility of an AI-Based Measure\nof the Hand Motions of Expert and Novice Surgeons. Comput Math\nMethods Med 2018; 2018: 9873273. doi:10.1155/2018/9873273\n[8] Alonso-Silverio GA, Pérez-Escamirosa F, Bruno-Sanchez R et al. Develop-\nment of a Laparoscopic Box Trainer Based on Open Source Hardware and\nArtificial Intelligence for Objective Assessment of Surgical Psychomotor\nSkills. Surg Innov 2018; 25: 380 –388. doi:10.1177/1553350618777045\n[9] Thalluri AL, Knox S, Nguyen T. MRI findings in deep infiltrating endome-\ntriosis: A pictorial essay. J Med Imaging Radiat Oncol 2017; 61: 767 –773.\ndoi:10.1111/1754-9485.12680\n[10] Loukas C, Varytimidis C, Rapantzikos K et al. Keyframe extraction from\nlaparoscopic videos based on visual saliency detection. Comput Methods\nPrograms Biomed 2018; 165: 13 –23. doi:10.1016/j.cmpb.2018.07.004\nKaya C et al. Telemedicine and Artificial ... Geburtsh Frauenheilk 2023; 83: 116 –117 | © 2022. The Author(s). 117","source_license":"CC0","license_restricted":false}