Artificial intelligence's current involvement in urology and future implementation in clinical environments

被引:0
|
作者
Zhao, Yi [1 ]
Bolton, Eva [2 ]
Soomro, Naeem [3 ]
Rai, Bhavan [3 ]
Heer, Rakesh [2 ]
机构
[1] Newham Univ Hosp, Glen Rd, London E13 8SL, England
[2] Charing Cross Hosp, London, England
[3] Freeman Rd Hosp, Newcastle Upon Tyne, England
关键词
Training; education; other; robotics; prostate cancer; SURGERY; PREDICT;
D O I
10.1177/20514158241300242
中图分类号
R5 [内科学]; R69 [泌尿科学(泌尿生殖系疾病)];
学科分类号
1002 ; 100201 ;
摘要
Artificial intelligence (AI) is a set of computational methods that interprets the data given, uncovers the underlying patterns associated with the complexity of data, and provides the prediction of outcomes that have become increasingly relevant in urology. The current application of AI in urology predominately focuses on disease diagnosis and risk factor analysis in urologic oncology and male infertility. While many candidate models have been proposed in the literature, efforts to construct clinically meaningful data by incorporating patient-specific and multidisciplinary approaches should be carried out to improve the clinical applicability of AI in driving personalised treatment planning and disease prognosis. Looking forward, AI has the potential to drive targeted training in urology, from surgical techniques to patient-specific surgical procedure simulation, in combination with other technologies such as augmented reality. In order to achieve this, patient involvement should be considered in the model development stage, which also addresses issues surrounding the ethical deployment of AI in the clinical environment. It is possible to see AI playing a collaborative role with surgeons in improving clinical efficiency in the future.Level of evidence: Not Applicable
引用
收藏
页数:5
相关论文
共 50 条
  • [21] Current and future applications of artificial intelligence in surgery: implications for clinical practice and research
    Morris, Miranda X.
    Fiocco, Davide
    Caneva, Tommaso
    Yiapanis, Paris
    Orgill, Dennis P.
    FRONTIERS IN SURGERY, 2024, 11
  • [22] Assessing the Efficacy and Clinical Utility of Artificial Intelligence Scribes in Urology
    Moryousef, Joseph
    Nadesan, Praveen
    Uy, Michael
    Matti, Danny
    Guo, Yanbo
    UROLOGY, 2025, 196 : 12 - 17
  • [23] Current and future implications of artificial intelligence in colonoscopy
    Antonelli, Giulio
    Rizkala, Tommy
    Iacopini, Federico
    Hassan, Cesare
    ANNALS OF GASTROENTEROLOGY, 2023, : 114 - 122
  • [24] Artificial Intelligence in Optometry: Current and Future Perspectives
    Krishnan, Anantha
    Dutta, Ananya
    Srivastava, Alok
    Konda, Nagaraju
    Prakasam, Ruby Kala
    CLINICAL OPTOMETRY, 2025, 17 : 83 - 114
  • [25] Current and Future Use of Artificial Intelligence in Electrocardiography
    Martinez-Selles, Manuel
    Marina-Breysse, Manuel
    JOURNAL OF CARDIOVASCULAR DEVELOPMENT AND DISEASE, 2023, 10 (04)
  • [26] Artificial intelligence in myopia: current and future trends
    Foo, Li Lian
    Ng, Wei Yan
    Lim, Gilbert Yong San
    Tan, Tien-En
    Ang, Marcus
    Ting, Daniel Shu Wei
    CURRENT OPINION IN OPHTHALMOLOGY, 2021, 32 (05) : 413 - 424
  • [27] Artificial Intelligence and Machine Learning in Radiology Current State and Considerations for Routine Clinical Implementation
    Wichmann, Julian L.
    Willemink, Martin J.
    De Cecco, Carlo N.
    INVESTIGATIVE RADIOLOGY, 2020, 55 (09) : 619 - 627
  • [28] Artificial intelligence: from challenges to clinical implementation
    Chassagnon, G.
    Dohan, A.
    DIAGNOSTIC AND INTERVENTIONAL IMAGING, 2020, 101 (12) : 763 - 764
  • [29] Exploring the interplay of clinical reasoning and artificial intelligence in psychiatry: Current insights and future directions
    Gauld, Christophe
    Martin, Vincent P.
    Bottemanne, Hugo
    Fourneret, Pierre
    Micoulaud-Franchi, Jean-Arthur
    Dumas, Guillaume
    PSYCHIATRY RESEARCH, 2024, 342
  • [30] Current status and future direction of cancer research using artificial intelligence for clinical application
    Hamamoto, Ryuji
    Komatsu, Masaaki
    Yamada, Masayoshi
    Kobayashi, Kazuma
    Takahashi, Masamichi
    Miyake, Mototaka
    Jinnai, Shunichi
    Koyama, Takafumi
    Kouno, Nobuji
    Machino, Hidenori
    Takahashi, Satoshi
    Asada, Ken
    Ueda, Naonori
    Kaneko, Syuzo
    CANCER SCIENCE, 2024,