Non-Moderated Poster Abstract
Eposter Presentation
https://storage.unitedwebnetwork.com/files/1237/323ff4457863ceae1ea80f0e1b89def8.pdf
Accept format: PDF. The file size should not be more than 5MB
https://storage.unitedwebnetwork.com/files/1237/5ce1be9d91b43457232db86420ee4531.png
Accept format: PNG/JPG/WEBP. The file size should not be more than 2MB
 
Submitted
Abstract
Artificial Intelligence in Urology - A Survey of Urology Healthcare Providers
Podium Abstract
Clinical Research
AI in Urology
Author's Information
10
No more than 10 authors can be listed (as per the Good Publication Practice (GPP) Guidelines).
Please ensure the authors are listed in the right order.
Australia
Yam Ting Ho jeremy.yt.ho@gmail.com Nepean Urology Research Group Urology Kingswood Australia *
Rizal Rian Dhalas dr.dhalas@gmail.com Dr. Soetomo Regional Public Hospital Urology Surabaya Indonesia
Muhammad Zohair doctorzohair1@gmail.com Institute of Kidney Diseases Hayatabad Urology Peshawar Pakistan
Subrata Deb dr.subrata27@gmail.com Sylhet MAG Osmani Medical College Hospital Urology Sylhet Bangladesh
Mohammed Shoaib doctr.shoaib@gmail.com Peshawar Medical College Urology Peshawar Pakistan
Sandra Elmer drsandraelmer@gmail.com Royal Melbourne Hospital Urology Melbourne Australia
Tauheed Fareed tauheedfareed786@hotmail.com Peshawar Institute of Medical Sciences/ Pak International Medical College Urology Peshawar Pakistan
Agus Rizal Ardy Hariandy Hamid rizalhamid.urology@gmail.com Cipto Mangunkusumo Hospital Urology Jakarta Indonesia
Jeremy YC Teoh jeremyteoh@surgery.cuhk.edu.hk Prince of Wales Hospital, The Chinese University of Hong Kong Surgery and Urology Hong Kong Hong Kong, China
Issac A Thangasamy ithangasamy@gmail.com Nepean Urology Research Group Urology Kingswood Australia
 
 
 
 
 
 
 
 
 
 
Abstract Content
To examine the attitude & beliefs about Artificial intelligence (AI) technology amongst urology health care providers. AI has many uses in medicine including but not limited to diagnostics, predicting clinical outcomes, and patient education. AI has been utilised in urological conditions such as urolithiasis, urogynaecology, and uro-oncology.
A structured online questionnaire, created from a modified Delphi method with a panel of urologists and urology surgical trainees, was delivered through the Urological Asia Association’s annual congress. The questionnaire, with 25 items of mixed type responses (five-point Likert scale, nominal polytomous and open-ended), acquired data regarding demographics, current and perceived AI usage, attitude/belief towards AI usage in urology, and perceived enablers & barriers with AI use.
464 respondents from 47 different countries over six continents were collected. 80% of participants have used AI in their practice and commonly used in research, patient education, and administrative tasks. More than 75% participants are positive towards AI and believe it will improve urological care and many believe AI adoption will not replace clinical practice. 86.2% of participants are willing to adopt AI in future clinical practice and identified the key enablers as regulatory approval, AI clinical effectiveness, and access to AI training.
Overall attitudes and beliefs toward the use of AI in urology is positive as participants see value in improving urological care. Nevertheless, further AI training and education, and regulatory reform are required to realise the full potential of AI in mainstream urology practice.
Artificial Intelligence, Urological care, Urological procedures
https://storage.unitedwebnetwork.com/files/1237/b8b4948dcf57263f998df01d6cefd11c.jpg
Table 1. Demographic details of respondents
https://storage.unitedwebnetwork.com/files/1237/8c0da2f3aa9c4ff806946bee4f1e3fc3.jpg
Table 2. Tabulated breakdown of responses for the question “Willingness to use AI in future practise”, organised by age group and occupation, presented as n (%)
 
 
 
 
 
 
1380
 
Presentation Details
 
 
 
0