Background In Hong Kong, one of six couples is affected by subfertility problems. Male infertility contributes to half of the infertility cases. In male infertility, there is no effective treatment for patients with idiopathic infertility/poor semen parameters. Recent meta-analysis results suggest that a traditional Chinese medicine (TCM) formula — Wuzi Yanzong pill — showed a curative effect on male fertility. However, the heterogeneity of the studies could not draw a definitive conclusion on the therapeutic effect of this formula. The aim of this study is to conduct a well-designed randomized controlled trial to investigate the effect of TCM formula Wuzi Yanzong pill on improving semen qualities in men with suboptimal parameters. Methods This study is a double-blinded, randomized placebo-controlled trial conducted in a public hospital in Hong Kong. Participants will be randomized, using computer-generated random numbers, with a 1:1 ratio to either the Wuzi Yanzong pill formula group or the placebo group. Both groups will be administered the drugs for 12 weeks. Participants will have a total of four visits for their semen and blood assessments for a 6-month period, and we will follow up for another 6 months to record their conception outcome. The primary outcome is to compare the total motile sperm count, natural conception rate, and pregnancy outcome to those under placebo treatment. Secondary objectives are sperm functions and assisted reproductive technology outcome. Discussion To date, there are no studies using the disclosed Wuzi Yanzong formula or double-blinded, randomized trials. The Wuzi Yanzong TCM formula may provide a good clinical solution for subfertile males for which contemporary western medicine has no cure. Therefore, a well-designed randomized trial for evaluating the effect of Wuzi Yanzong TCM formula is urgently needed. Trial registration Chinese Clinical Trial Registry (ChiCTR), ChiCTR-INR-17010790 . Registered on 27 February 2017. Centre for Clinical Research and Biostatistics - Clinical Trials Registry, CUHK_CCRB00548 . Registered on 27 February 2017. Electronic supplementary material The online version of this article (10.1186/s13063-019-3647-2) contains supplementary material, which is available to authorized users.

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Selection of the best quality embryo is the key for a faithful implantation in in vitro fertilization (IVF) practice. However, the process of evaluating numerous images captured by time‐lapse imaging (TLI) system is time‐consuming and some important features cannot be recognized by naked eyes. Convolutional neural network (CNN) is used in medical imaging yet in IVF. The study aims to apply CNN on day‐one human embryo TLI. We first presented CNN algorithm for day‐one human embryo segmentation on three distinct features: zona pellucida (ZP), cytoplasm and pronucleus (PN). We tested the CNN performance compared side‐by‐side with manual labelling by clinical embryologist, then measured the segmented day‐one human embryo parameters and compared them with literature reported values. The precisions of segmentation were that cytoplasm over 97%, PN over 84% and ZP around 80%. For the morphometrics data of cytoplasm, ZP and PN, the results were comparable with those reported in literatures, which showed high reproducibility and consistency. The CNN system provides fast and stable analytical outcome to improve work efficiency in IVF setting. To conclude, our CNN system is potential to be applied in practice for day‐one human embryo segmentation as a robust tool with high precision, reproducibility and speed.

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