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Applications of artificial intelligence in the diagnosis and prediction of erectile dysfunction: a narrative review

International Journal of Impotence Research volume 35, pages 95–102 (2023)Cite this article

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Abstract

Despite the high prevalence of erectile dysfunction, patients are reluctant to seek medical advice, which leads to low diagnostic rates in clinical practice. Artificial intelligence has been widely applied in the diagnosis of many diseases and may alleviate the situation. However, the applications of artificial intelligence in erectile dysfunction have not been reviewed to date. Therefore, the assistance from artificial intelligence needs to be summarized. In this review, 418 publications before January 10, 2021, regarding artificial intelligence applications in diagnosing and predicting erectile dysfunction, were retrieved from five databases, including PubMed, EMBASE, the Cochrane Library, and two Chinese databases (WANFANG and CNKI). In addition, the reference lists of the included studies or relevant reviews were checked to avoid bias. Finally, 30 articles were reviewed to summarize the current status, merits, and limitations of applying artificial intelligence in diagnosing and predicting erectile dysfunction. The results showed that artificial intelligence contributed to developing novel diagnostic questionnaires, equipment, expert systems, classifiers by images and predictive models. However, most of the included studies were not subjected to external validations, resulting in doubt on the generalizability. In the future, more rigorously designed studies with high-quality datasets for erectile dysfunction are required.

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Funding

This work was supported by the Natural Science Foundation of China [grant numbers 81871147 and 81671453]; and the funding of Health Commission of Sichuan Province [grant numbers 20PJ184 and 20PJ063].

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Authors and Affiliations

  1. Andrology Laboratory, West China Hospital, Sichuan University, Chengdu, China

    Yang Xiong, Fuxun Zhang, Changjing Wu, Feng Qin & Jiuhong Yuan

  2. Department of Urology, West China Hospital, Sichuan University, Chengdu, China

    Yang Xiong, Fuxun Zhang & Jiuhong Yuan

  3. Department of Epidemiology and Health Statistics, School of Public Health and Management, Chongqing Medical University, Chongqing, China

    Yangchang Zhang

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  1. Yang Xiong
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Contributions

Conception and design: YX, FQ, and JY. Administrative support: FQ and JY. Provision of study materials or patients: YX and FQ. Collection and assembly of data: YX, FQ, and YZ. Data analysis and interpretation: YX, YZ, FZ, and CW. Manuscript writing: all authors. Final approval of manuscript: all authors.

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Correspondence to Jiuhong Yuan.

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Xiong, Y., Zhang, Y., Zhang, F. et al. Applications of artificial intelligence in the diagnosis and prediction of erectile dysfunction: a narrative review. Int J Impot Res 35, 95–102 (2023). https://doi.org/10.1038/s41443-022-00528-w

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