ReviewDiagnostics (Basel, Switzerland)2021
Artificial Intelligence and Machine Learning in Prostate Cancer Patient Management-Current Trends and Future Perspectives.
Review in Diagnostics (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT06565923 (Study on the Staging and Prognosis Model of Bladder Cancer Based on Artificial Intelligence and Multimodal Omics Features), which is not on this map. Cited by 76 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.
Study on the Staging and Prognosis Model of Bladder Cancer Based on Artificial Intelligence and Multimodal Omics Features
Who cites it
76 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Inter-reader agreement of the prostate imaging reporting and data system version v2.1 for detection of prostate cancer: A systematic review and meta-analysis.Frontiers in oncology · 2022Pooled it
- Trial
- AnCurrent radiopharmaceuticals · 2024Trial
- Leveraging Artificial Intelligence to Monitor Patients With Prostate Cancer in a Retrospective Cohort of Radiation Oncology Clinic Patients.Clinical journal of oncology nursing · 2026Article
- A machine learning-based basement membrane gene signature model for predicting ovarian cancer survival.Translational cancer research · 2026Article
- Screening policy changes and prostate cancer epidemiology: 20-year trends in diagnosis, treatment, incidence, and mortality.World journal of urology · 2026Article
- Article
- Healthcare Providers' Perspectives on Generative Artificial Intelligence (GenAI) Adoption, Adaptation, Assimilation, and Use in the United States.Healthcare (Basel, Switzerland) · 2026Article
- Exploring advancements in the management of penile cancer in the era of artificial intelligence and machine learning: a narrative review.Annals of medicine and surgery (2012) · 2026Article
- Multimodal artificial intelligence in urologic precision oncology: from algorithm to translational medicine (a systemized narrative review).Frontiers in oncology · 2026Review
- Artificial Intelligence Across the Prostate Cancer Pathway: Screening, Imaging, Pathology, and Biomarkers.Cureus · 2025Review
- Machine learning-based prediction of post-operative outcomes in robotic-assisted radical prostatectomy: a multi-variable analysis of 758 cases.Journal of robotic surgery · 2025Article
- POC Sensor Systems and Artificial Intelligence-Where We Are Now and Where We Are Going?Biosensors · 2025Review
- Mitigating bias in prostate cancer diagnosis using synthetic data for improved AI driven Gleason grading.NPJ precision oncology · 2025Article
- Prediction of Prostate Cancer From Routine Laboratory Markers With Automated Machine Learning.Journal of clinical laboratory analysis · 2025Article
- A prognostic model for highly aggressive prostate cancer using interpretable machine learning techniques.Frontiers in medicine · 2025Article
- A Review of Novel Cancer Therapeutics and Current Research Trends.TheScientificWorldJournal · 2025Review
- Review of different convolutional neural networks used in segmentation of prostate during fusion biopsy.Central European journal of urology · 2025Review
- Perceptions and attitudes towards AI among trainee and qualified radiologists at selected South African training hospitals.SA journal of radiology · 2025Article
- Machine Learning-Based Prediction of Prostate Biopsy Necessity Using PSA, MRI, and Hematologic Parameters.Journal of clinical medicine · 2024Article
16 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
15 authors.
Funding
Abstract
Artificial intelligence (AI) is the field of computer science that aims to build smart devices performing tasks that currently require human intelligence. Through machine learning (ML), the deep learning (DL) model is teaching computers to learn by example, something that human beings are doing naturally. AI is revolutionizing healthcare. Digital pathology is becoming highly assisted by AI to help researchers in analyzing larger data sets and providing faster and more accurate diagnoses of prostate cancer lesions. When applied to diagnostic imaging, AI has shown excellent accuracy in the detection of prostate lesions as well as in the prediction of patient outcomes in terms of survival and treatment response. The enormous quantity of data coming from the prostate tumor genome requires fast, reliable and accurate computing power provided by machine learning algorithms. Radiotherapy is an essential part of the treatment of prostate cancer and it is often difficult to predict its toxicity for the patients. Artificial intelligence could have a future potential role in predicting how a patient will react to the therapy side effects. These technologies could provide doctors with better insights on how to plan radiotherapy treatment. The extension of the capabilities of surgical robots for more autonomous tasks will allow them to use information from the surgical field, recognize issues and implement the proper actions without the need for human intervention.
Indexed as
Identifiers
What OpenQuestion holds
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.