ArticleProstate international2022
Dr. Answer AI for prostate cancer: Intention to use, expected effects, performance, and concerns of urologists.
Article in Prostate international, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 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
2 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Healthcare professionals' perspectives on artificial intelligence in patient care: a systematic review of hindering and facilitating factors on different levels.BMC health services research · 2025Pooled it
- Artificial intelligence in urologic oncology: the actual clinical practice results of IBM Watson for Oncology in South Korea.Prostate international · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objectives: To efficiently implement artificial intelligence (AI) software for medical applications, it is crucial to understand the acceptance, expected effects, expected performance, and concerns of software users. In this study, we examine the acceptance and expectation of the Dr. Answer AI software for prostate cancer. Methods: We conducted an online survey for urologists from August 13 to September 18, 2020. The target software is an AI-based clinical software called Dr. Answer AI software, used for prostate cancer diagnosis. We collected data from 86 urologists and conducted a basic statistical and multiple regression analysis using the R package. Results: The compatibility was significantly associated with the intention to use the Dr. Answer AI software. The expected average accuracy for the software ranges from 86.91% to 87.51%, and the urologists perceived that the cloud method is suitable to introduce the software. The most desirable function of the software for the specialists is predicting the occurrence of extracapsular extension, seminal vesicle invasion, and lymph node metastasis after radical prostatectomy. Finally, the primary concerns involved the cost, compatibility with existing systems, and obtaining accurate information from the software. Conclusions: Our results present an understanding of the acceptance, expected effects, expected performance, and concerns of software users. The results provide a guide to help AI software be properly developed and implemented in medical applications.
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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.