Emergence of artificial generative intelligence and its potential impact on urology

被引:0
|
作者
Javid, Mohamed [1 ]
Reddiboina, Madhu [2 ]
Bhandari, Mahendra [3 ]
机构
[1] Chengalpattu Med Coll, Dept Urol, Chengalpattu, India
[2] RediMinds Inc, Southfield, MI USA
[3] Vattikuti Urol Inst, Henry Ford Hosp, Detroit, MI USA
关键词
artificial intelligence; artificial generative intelligence; large-language models; urology; ChatGPT; Med-PaLM; 2; BARD;
D O I
暂无
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
Introduction: Artificial generative intelligence (AGI) and large language models (LLMs) have gained significant attention in healthcare and hold enormous promise for transforming every aspect of our life and urology is no exception. Materials and methods: We conducted a comprehensive literature search of electronic databases and included articles discussing AGI and LLMs in healthcare. Additionally, we have incorporated our experiences interacting with the ChatGPT and GPT-4 in different situations with real case reports and case constructs. Results: Our review highlights the potential applications and likely impact of these technologies in urology, for differential diagnosis, prioritizing treatment options, and facilitating research, surgeon, and patient education. At their current developmental stage, we have recognized the need for concurrent validation and continuous human interaction necessary to induce inverse reinforced learning with human feedback to mature them to authenticity. We need to consciously adjust to the hallucinations and guard patients' confidentiality before their extensive implementations in clinical practice. We propose possible remedies for these shortcomings and emphasize the critical role of human interaction in their evolution. Conclusion: The integration of these tools has the potential to revolutionize urology, but it also presents several challenges needing attention. To harness the full potential of these models, urologists must consistently engage in training these tools with their clinical sense and experience. We urge the urology community to actively participate in AGI and LLM development to address potential challenges. These models could help us in unleashing our full potential and help us achieve a better work-life balance.
引用
收藏
页码:11588 / 11598
页数:11
相关论文
共 50 条
  • [41] Analysis Generative artificial intelligence
    Stokel-Walker, Chris
    NEW SCIENTIST, 2024, 247 (3492) : 18 - 18
  • [42] Generative Artificial Intelligence: Fundamentals
    Corchado, Juan M.
    Lopez, F. Sebastian
    Nunez, V. Juan M.
    Garcia, S. Raul
    Chamoso, Pablo
    ADCAIJ-ADVANCES IN DISTRIBUTED COMPUTING AND ARTIFICIAL INTELLIGENCE JOURNAL, 2023, 12 (01):
  • [43] Generative artificial intelligence in ophthalmology
    Waisberg, Ethan
    Ong, Joshua
    Kamran, Sharif Amit
    Masalkhi, Mouayad
    Paladugu, Phani
    Zaman, Nasif
    Lee, Andrew G.
    Tavakkoli, Alireza
    SURVEY OF OPHTHALMOLOGY, 2025, 70 (01) : 1 - 11
  • [44] On Chatbots and Generative Artificial Intelligence
    Oermann, Eric Karl
    Kondziolka, Douglas
    NEUROSURGERY, 2023, 92 (04) : 665 - 666
  • [45] Generative Artificial Intelligence and ChatGPT
    Byrne, Matthew D.
    JOURNAL OF PERIANESTHESIA NURSING, 2023, 38 (03) : 519 - 522
  • [46] Generative artificial intelligence in oncology
    Ganjavi, Conner
    Melamed, Sam
    Biedermann, Brett
    Eppler, Michael B.
    Rodler, Severin
    Layne, Ethan
    Cei, Francesco
    Gill, Inderbir
    Cacciamani, Giovanni E.
    CURRENT OPINION IN UROLOGY, 2025, 35 (03) : 205 - 213
  • [47] Generative artificial intelligence and surgeons
    Lai, Paul B. S.
    SURGICAL PRACTICE, 2023, 27 (03) : 128 - 130
  • [48] A Primer on Generative Artificial Intelligence
    Kalota, Faisal
    EDUCATION SCIENCES, 2024, 14 (02):
  • [49] Artificial Intelligence in Urology: The Final Frontier?
    Loughlin, Kevin R.
    UROLOGIC CLINICS OF NORTH AMERICA, 2024, 51 (01) : XI - XII
  • [50] Is Artificial Intelligence Ready for "Primetime" in Urology?
    Eardly, Ian
    BJU INTERNATIONAL, 2021, 128 (06) : 659 - 660