TY - JOUR
T1 - Artificial Intelligence in Andrology: From Semen Analysis to Image Diagnostics
AU - Widi Atmoko
AU - Ghayda, Ramy abou
AU - Cannarella, Rossella
AU - Calogero, Aldo e.
AU - Shah, Rupin
AU - Rambhatla, Amarnath
AU - Zohdy, Wael
AU - Kavoussi, Parviz
AU - Avidor-Reiss, Tomer
AU - Boitrelle, Florence
AU - Mostafa, Taymour
AU - Saleh, Ramadan
AU - Toprak, Tuncay
AU - Birowo, Ponco
AU - Salvio, Gianmaria
AU - Calik, Gokhan
AU - Kuroda, Shinnosuke
AU - Kaiyal, Raneen sawaid
AU - Ziouziou, Imad
AU - Crafa, Andrea
AU - Phuoc, Nguyen ho vinh
AU - Russo, Giorgio i.
AU - Durairajanayagam, Damayanthi
AU - Al-Hashimi, Manaf
AU - Hamoda, Taha abo-Almagd abdel-Meguid
AU - Pinggera, Germar-Michael
AU - Adriansjah, Ricky
AU - Rosas, Israel maldonado
AU - Arafa, Mohamed
AU - Chung, Eric
AU - Atmoko, Widi
AU - Rocco, Lucia
AU - Lin, Haocheng
AU - Huyghe, Eric
AU - Kothari, Priyank
AU - Vazquez, Jesus fernando solorzano
AU - Dimitriadis, Fotios
AU - Garrido, Nicolas
AU - Homa, Sheryl
AU - Falcone, Marco
AU - Sabbaghian, Marjan
AU - Kandil, Hussein
AU - Ko, Edmund
AU - Martinez, Marlon
AU - Nguyen, Quang
AU - Harraz, Ahmed m.
AU - Serefoglu, Ege can
AU - Karthikeyan, Vilvapathy senguttuvan
AU - Tien, Dung mai ba
AU - Jindal, Sunil
AU - Micic, Sava
PY - 2023
Y1 - 2023
N2 - Artificial intelligence (AI) in medicine has gained a lot of momentum in the last decades and has been applied to various fields of medicine. Advances in computer science, medical, informatics, robotics, and the need for personalized medicine have facilitated the role of AI in modern healthcare. Similarly, as in other fields, AI applications, such as machine learning, artificial neural networks, and deep learning, have shown great potential in andrology and reproductive medicine. AI-based tools are poised to become valuable assets with abilities to support and aid in diagnosing and treating male infertility, and in improving the accuracy of patient care. These automated, AI-based predictions may offer consistency and efficiency in terms of time and cost in infertility research and clinical management. In andrology and reproductive medicine, AI has been used for objective sperm, oocyte, and embryo selection, prediction of surgical outcomes, cost-effective assessment, development of robotic surgery, and clinical decision-making systems. In the future, better integration and implementation of AI into medicine will undoubtedly lead to pioneering evidence-based breakthroughs and the reshaping of andrology and reproductive medicine.
AB - Artificial intelligence (AI) in medicine has gained a lot of momentum in the last decades and has been applied to various fields of medicine. Advances in computer science, medical, informatics, robotics, and the need for personalized medicine have facilitated the role of AI in modern healthcare. Similarly, as in other fields, AI applications, such as machine learning, artificial neural networks, and deep learning, have shown great potential in andrology and reproductive medicine. AI-based tools are poised to become valuable assets with abilities to support and aid in diagnosing and treating male infertility, and in improving the accuracy of patient care. These automated, AI-based predictions may offer consistency and efficiency in terms of time and cost in infertility research and clinical management. In andrology and reproductive medicine, AI has been used for objective sperm, oocyte, and embryo selection, prediction of surgical outcomes, cost-effective assessment, development of robotic surgery, and clinical decision-making systems. In the future, better integration and implementation of AI into medicine will undoubtedly lead to pioneering evidence-based breakthroughs and the reshaping of andrology and reproductive medicine.
U2 - 10.5534/wjmh.230050
DO - 10.5534/wjmh.230050
M3 - Article
SN - 2287-4208
VL - 41
JO - World Journal of Men?s Health
JF - World Journal of Men?s Health
ER -