Artificial Intelligence in Andrology: From Semen Analysis to Image Diagnostics

Data de publicació: 01/01/2024 Data Ahead of Print: 01/06/2023

Autors de IIS La Fe

Nicolás Garrido Puchalt

Autor

Autors aliens a IIS La Fe

Ghayda, Ramy Abou
Cannarella, Rossella
Calogero, Aldo E.
Shah, Rupin
Rambhatla, Amarnath
Zohdy, Wael
Kavoussi, Parviz
Avidor-Reiss, Tomer
Boitrelle, Florence
Mostafa, Taymour
Saleh, Ramadan
Toprak, Tuncay
Birowo, Ponco
Salvio, Gianmaria
Calik, Gokhan
Kuroda, Shinnosuke
Kaiyal, Raneen Sawaid
Ziouziou, Imad
Crafa, Andrea
Phuoc, Nguyen Ho Vinh
Russo, Giorgio I.
Durairajanayagam, Damayanthi
Al-Hashimi, Manaf
Hamoda, Taha Abo-Almagd Abdel-Meguid
Pinggera, Germar-Michael
Adriansjah, Ricky
Maldonado Rosas, Israel
Arafa, Mohamed
Chung, Eric
Atmoko, Widi
Rocco, Lucia
Lin, Haocheng
Huyghe, Eric
Kothari, Priyank
Solorzano Vazquez, Jesus Fernando
Dimitriadis, Fotios
Homa, Sheryl
Falcone, Marco
Sabbaghian, Marjan
Kandil, Hussein
Ko, Edmund
Martinez, Marlon
Nguyen, Quang
Harraz, Ahmed M.
Serefoglu, Ege Can
Karthikeyan, Vilvapathy Senguttuvan
Tien, Dung Mai Ba
Jindal, Sunil
Micic, Sava
Bellavia, Marina
Alali, Hamed
Gherabi, Nazim
Lewis, Sheena
Park, Hyun Jun
Simopoulou, Mara
Sallam, Hassan
Ramirez, Liliana
Colpi, Giovanni
Agarwal, Ashok
Global Andrology Forum

Grups d'Investigació

Biología Reproductiva y Bioingeniería en Reproducción Humana

Leader

Nicolás Garrido Puchalt

Abstract

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.