ArticleCommunications biology2019
Deep learning-based selection of human sperm with high DNA integrity.
Article in Communications biology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 41 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
41 citing papers in PubMed, 1 synthesis or guideline pooled it, 124 citations in OpenAlex.
- Use of Artificial Intelligence in the choice of sperm for ICSI - A Literature Review.JBRA assisted reproduction · 2026Pooled it
- AI-enabled precision reproductive medicine: a comprehensive review of clinical applications, decision frameworks, and evidence-based implementation.Journal of assisted reproduction and genetics · 2026Review
- Integrating Sperm Microscopy, Environmental Exposures, and Lifestyle Factors for Male Fertility Analysis: Protocol for the Nippon Semen and Environmental Exposure Database (N-SEED) Cross-Sectional Study.JMIR research protocols · 2026Article
- Epidemiology, Etiopathogenesis, Diagnosis, and Treatment of Male Infertility-Current Trends and Future Directions: A Narrative Review.Medicina (Kaunas, Lithuania) · 2026Review
- The potential, perils and pitfalls of Artificial intelligence (AI) in Assisted Reproductive Technologies (ART).Reproductive biology and endocrinology : RB&E · 2026Review
- Treatment management algorithm for natural frozen embryo transfer cycles using a real-time ovulation prediction machine learning model.Scientific reports · 2026Article
- Deep learning-based morphological analysis of human sperm.Medical & biological engineering & computing · 2026Article
- Evaluation of Sperm Quality by Flow Cytometry: Sequential Protocols for DNA Fragmentation and Acrosome Reaction in Membrane-Intact Spermatozoa.Methods in molecular biology (Clifton, N.J.) · 2026Article
- The role of sperm DNA fragmentation in reproduction: a SWOT analysis.Journal of assisted reproduction and genetics · 2025Review
- Deep learning-based approach for sperm morphology analysis.BMC urology · 2025Review
- 3D+t Multifocal Imaging Dataset of Human Sperm.Scientific data · 2025Article
- Detection of sperm DNA damage in male infertility patients and evaluation of Levocarnitine efficacy using sperm chromatin diffusion (SCD) and AI-DFI methods: a cross-sectional study.European journal of medical research · 2025Article
- [Advances in the Application of Artificial Intelligence in the Field of Male Infertility].Sichuan da xue xue bao. Yi xue ban = Journal of Sichuan University. Medical science edition · 2025Review
- Fluo-Cast-Bright: a deep learning pipeline for the non-invasive prediction of chromatin structure and developmental potential in live oocytes.Communications biology · 2025Article
- Current and Future Applications of Artificial Intelligence to Diagnose and Treat Male Infertility.Advances in experimental medicine and biology · 2025Review
- Automatic identification of human spermatozoa with zona pellucida-binding capability using deep learning.Human reproduction open · 2025Article
- Artificial Intelligence, Clinical Decision Support Algorithms, Mathematical Models, Calculators Applications in Infertility: Systematic Review and Hands-On Digital Applications.Mayo Clinic proceedings. Digital health · 2024Review
- Improved clinical pregnancy rates in natural frozen-thawed embryo transfer cycles with machine learning ovulation prediction: insights from a retrospective cohort study.Scientific reports · 2024Article
- A narrative review of sperm selection technology for assisted reproduction techniques.Translational andrology and urology · 2024Review
- [Application of Artificial Intelligence in Sperm Quality Analysis and Sperm Screening].Sichuan da xue xue bao. Yi xue ban = Journal of Sichuan University. Medical science edition · 2024Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors at 2 institutions in 1 country.
Funding
Abstract
Despite the importance of sperm DNA to human reproduction, currently no method exists to assess individual sperm DNA quality prior to clinical selection. Traditionally, skilled clinicians select sperm based on a variety of morphological and motility criteria, but without direct knowledge of their DNA cargo. Here, we show how a deep convolutional neural network can be trained on a collection of ~1000 sperm cells of known DNA quality, to predict DNA quality from brightfield images alone. Our results demonstrate moderate correlation (bivariate correlation ~0.43) between a sperm cell image and DNA quality and the ability to identify higher DNA integrity cells relative to the median. This deep learning selection process is directly compatible with current, manual microscopy-based sperm selection and could assist clinicians, by providing rapid DNA quality predictions (under 10 ms per cell) and sperm selection within the 86
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.