ArticleCurrent opinion in biomedical engineering2017
Computer-aided diagnosis of prostate cancer with MRI.
Article in Current opinion in biomedical engineering, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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
12 citing papers in PubMed, 35 citations in OpenAlex.
- A General Bayesian Functional Spatial Partitioning Method for Multiple Region Discovery Applied to Prostate Cancer MRI.Bayesian analysis · 2024Article
- Diffusion kurtosis imaging and standard diffusion imaging in the magnetic resonance imaging assessment of prostate cancer.Gland surgery · 2023Review
- Multi-resolution super learner for voxel-wise classification of prostate cancer using multi-parametric MRI.Journal of applied statistics · 2023Article
- Review
- Comparison of machine learning models based on multi-parametric magnetic resonance imaging and ultrasound videos for the prediction of prostate cancer.Frontiers in oncology · 2023Article
- Machine Learning in Prostate MRI for Prostate Cancer: Current Status and Future Opportunities.Diagnostics (Basel, Switzerland) · 2022Review
- Precise Identification of Prostate Cancer from DWI Using Transfer Learning.Sensors (Basel, Switzerland) · 2021Article
- Effect of domain knowledge encoding in CNN model architecture-a prostate cancer study using mpMRI images.PeerJ · 2021Article
- Article
- Multiparametric MRI and auto-fixed volume of interest-based radiomics signature for clinically significant peripheral zone prostate cancer.European radiology · 2020Article
- Evolution of prostate MRI: from multiparametric standard to less-is-better and different-is better strategies.European radiology experimental · 2019Review
- Detection of Dominant Intra-prostatic Lesions in Patients With Prostate Cancer Using an Artificial Neural Network and MR Multi-modal Radiomics Analysis.Frontiers in oncology · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author at 1 institution in 1 country.
Funding
Abstract
Multi-parametric magnetic resonance imaging (mp-MRI) has an increasingly important role in the diagnosis of prostate cancer. Due to the large amount of data and variations in mp-MRI, tumor detection can be affected by multiple factors, such as the observer's clinical experience, image quality, and appearance of the lesions. In order to improve the quantitative assessment of the disease and reduce the reporting time, various computer-aided diagnosis (CAD) systems have been designed to help radiologists identify lesions. This manuscript presents an overview of the literature regarding prostate CAD using mp-MRI, while focusing on the studies of the most recent five years. Current prostate CAD technologies and their utilization are discussed in this review.
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.