1. Web- and Artificial Intelligence–Based Image Recognition For Sperm Motility Analysis: Verification Study
- Author
-
Tsai, Vincent FS, Zhuang, Bin, Pong, Yuan-Hung, Hsieh, Ju-Ton, and Chang, Hong-Chiang
- Subjects
Computer applications to medicine. Medical informatics ,R858-859.7 - Abstract
BackgroundHuman sperm quality fluctuates over time. Therefore, it is crucial for couples preparing for natural pregnancy to monitor sperm motility. ObjectiveThis study verified the performance of an artificial intelligence–based image recognition and cloud computing sperm motility testing system (Bemaner, Createcare) composed of microscope and microfluidic modules and designed to adapt to different types of smartphones. MethodsSperm videos were captured and uploaded to the cloud with an app. Analysis of sperm motility was performed by an artificial intelligence–based image recognition algorithm then results were displayed. According to the number of motile sperm in the vision field, 47 (deidentified) videos of sperm were scored using 6 grades (0-5) by a male-fertility expert with 10 years of experience. Pearson product-moment correlation was calculated between the grades and the results (concentration of total sperm, concentration of motile sperm, and motility percentage) computed by the system. ResultsGood correlation was demonstrated between the grades and results computed by the system for concentration of total sperm (r=0.65, P
- Published
- 2020
- Full Text
- View/download PDF