Artificial intelligence and augmented reality in gynecology

被引:17
作者
Moawad, Gaby [1 ]
Tyan, Paul [2 ]
Louie, Michelle [2 ]
机构
[1] George Washington Univ Hosp, Dept Obstet & Gynecol, Div Minimally Invas Gynecol Surg, Washington, DC USA
[2] Univ N Carolina, Sch Med, Dept Obstet & Gynecol, Div Minimally Invas Gynecol Surg, Chapel Hill, NC 27515 USA
关键词
artificial intelligence; augmented reality; deep learning; gynecologic surgery; machine learning; INDOCYANINE GREEN; URINARY PATHWAYS;
D O I
10.1097/GCO.0000000000000559
中图分类号
R71 [妇产科学];
学科分类号
100211 ;
摘要
Purpose of review Artificial intelligence and augmented reality have been progressively incorporated into our daily life. Technological advancements have resulted in the permeation of similar systems into medical practice. Recent findings Both artificial intelligence and augmented reality are being increasingly incorporated into the practice of modern medicine to optimize decision making and ultimately improve patient outcomes. Artificial intelligence has already been incorporated into many areas of medical practice but has been slow to catch on in clinical gynecology. However, several applications of augmented reality are currently in use in gynecologic surgery. We present an overview of artificial intelligence and augmented reality and current use in medical practice with a focus on gynecology.
引用
收藏
页码:345 / 348
页数:4
相关论文
共 27 条
[11]   Computer-aided classification of lung nodules on computed tomography images via deep learning technique [J].
Hua, Kai-Lung ;
Hsu, Che-Hao ;
Hidayati, Hintami Chusnul ;
Cheng, Wen-Huang ;
Chen, Yu-Jen .
ONCOTARGETS AND THERAPY, 2015, 8 :2015-2022
[12]   Using Artificial Intelligence to Reduce the Risk of Nonadherence in Patients on Anticoagulation Therapy [J].
Labovitz, Daniel L. ;
Shafner, Laura ;
Gil, Morayma Reyes ;
Virmani, Deepti ;
Hanina, Adam .
STROKE, 2017, 48 (05) :1416-+
[13]  
Li L., 2016, PLoS One, V11, P1, DOI DOI 10.1371/JOURNAL.PONE.0144219
[14]   Improving accuracy of intraoperative diagnosis of endometriosis: Role of firefly in minimal access robotic surgery [J].
Lue, John R. ;
Pyrzak, Adam ;
Allen, Jennifer .
JOURNAL OF MINIMAL ACCESS SURGERY, 2016, 12 (02) :186-189
[15]   The safety and feasibility of minimally invasive sentinel lymph node staging using indocyanine green in the management of endometrial cancer [J].
Mendivil, Alberto A. ;
Abaid, Lisa N. ;
Brown, John V., III ;
Mori, Kristina M. ;
Beck, Tiffany L. ;
Epstein, Howard D. ;
Micha, John R. ;
Goldstein, Bram H. .
EUROPEAN JOURNAL OF OBSTETRICS & GYNECOLOGY AND REPRODUCTIVE BIOLOGY, 2018, 224 :29-32
[16]   A novel rotational matrix and translation vector algorithm: geometric accuracy for augmented reality in oral and maxillofacial surgeries [J].
Murugesan, Yahini Prabha ;
Alsadoon, Abeer ;
Manoranjan, Paul ;
Prasad, P. W. C. .
INTERNATIONAL JOURNAL OF MEDICAL ROBOTICS AND COMPUTER ASSISTED SURGERY, 2018, 14 (03)
[17]   Prediction of 5-year overall survival in cervical cancer patients treated with radical hysterectomy using computational intelligence methods [J].
Obrzut, Bogdan ;
Kusy, Maciej ;
Semczuk, Andrzej ;
Obrzut, Marzanna ;
Kluska, Jacek .
BMC CANCER, 2017, 17
[18]   Imaging the urinary pathways in mice by liposomal indocyanine green [J].
Portnoy, Emma ;
Nizri, Eran ;
Golenser, Jacob ;
Shmuel, Miriam ;
Magdassi, Shlomo ;
Eyal, Sara .
NANOMEDICINE-NANOTECHNOLOGY BIOLOGY AND MEDICINE, 2015, 11 (05) :1057-1064
[19]   Role of artificial intelligence in the care of patients with nonsmall cell lung cancer [J].
Rabbani, Mohamad ;
Kanevsky, Jonathan ;
Kafi, Kamran ;
Chandelier, Florent ;
Giles, Francis J. .
EUROPEAN JOURNAL OF CLINICAL INVESTIGATION, 2018, 48 (04)
[20]   Deep learning [J].
Rusk, Nicole .
NATURE METHODS, 2016, 13 (01) :35-35