Final Gleason score prediction using discriminant analysis and support vector machine based on preoperative multiparametric MR imaging of prostate cancer at 3T.

scientific article published on 2 December 2014

Final Gleason score prediction using discriminant analysis and support vector machine based on preoperative multiparametric MR imaging of prostate cancer at 3T. is …
instance of (P31):
scholarly articleQ13442814

External links are
P356DOI10.1155/2014/690787
P932PMC publication ID4269213
P698PubMed publication ID25544944
P5875ResearchGate publication ID270221424

P50authorMetin VuralQ84526027
Esin Ozturk-IsikQ39068177
P2093author name stringTarik Esen
Omer Acar
Aslihan Onay
Fusun Citak-Er
P2860cites workComputer-aided diagnosis of prostate cancer in the peripheral zone using multiparametric MRIQ84234501
ESUR prostate MR guidelines 2012Q24620926
Prostate cancer detection and diagnosis: the role of MR and its comparison with other diagnostic modalities--a radiologist's perspectiveQ30422070
Computer-assisted diagnosis of prostate cancer using DCE-MRI data: design, implementation and preliminary resultsQ33520713
Histologic grading of prostate cancer: a perspectiveQ35959663
A practical guide to prostate cancer diagnosis and managementQ37871230
Multiparametric MRI and prostate cancer diagnosis and risk stratificationQ38012217
Overview of dynamic contrast-enhanced MRI in prostate cancer diagnosis and management.Q38012717
Quantitative analysis of multiparametric prostate MR images: differentiation between prostate cancer and normal tissue and correlation with Gleason score--a computer-aided diagnosis development study.Q38080001
Prostate Cancer: Screening, Diagnosis, and ManagementQ40486134
Multiparametric MRI maps for detection and grading of dominant prostate tumors.Q41083513
MRI in the detection of prostate cancer: combined apparent diffusion coefficient, metabolite ratio, and vascular parameters.Q43236780
Role of magnetic resonance spectroscopic imaging ([¹H]MRSI) and dynamic contrast-enhanced MRI (DCE-MRI) in identifying prostate cancer foci in patients with negative biopsy and high levels of prostate-specific antigen (PSA).Q45568949
Incremental kernel principal component analysis.Q45965345
Primary Gleason pattern in biopsy Gleason score 7 is predictive of adverse histopathological features and biochemical failure following radical prostatectomyQ47929289
Preoperative neural network using combined magnetic resonance imaging variables, prostate specific antigen and Gleason score to predict prostate cancer stageQ50769148
Prostate Cancer Detection on Dynamic Contrast-Enhanced MRI: Computer-Aided Diagnosis Versus Single Perfusion Parameter MapsQ53195259
Support-vector networksQ55922708
Gene Selection for Cancer Classification using Support Vector MachinesQ56535529
Survival Benefit of Radical Prostatectomy in Patients with Localized Prostate Cancer: Estimations of the Number Needed to Treat According to Tumor and Patient CharacteristicsQ59649541
Combined use of diffusion-weighted MRI and 1H MR spectroscopy to increase accuracy in prostate cancer detectionQ79441999
Computerized analysis of prostate lesions in the peripheral zone using dynamic contrast enhanced MRIQ81061744
Gleason grading of prostate cancer. Contemporary approachQ82393915
Time Trends in Prostate Cancer Mortality Between 1950 and 2008 in Japan, the USA and Europe Based on the WHO Mortality DatabaseQ82737263
[The role of diffusion 3-Tesla MRI in detecting prostate cancer before needle biopsy: multiparametric study of 111 patients]Q82999281
Computer-assisted analysis of peripheral zone prostate lesions using T2-weighted and dynamic contrast enhanced T1-weighted MRIQ83106413
P275copyright licenseCreative Commons Attribution 3.0 UnportedQ14947546
P6216copyright statuscopyrightedQ50423863
P407language of work or nameEnglishQ1860
P921main subjectsupport vector machineQ282453
P304page(s)690787
P577publication date2014-12-02
P1433published inBioMed Research InternationalQ17509958
P1476titleFinal Gleason score prediction using discriminant analysis and support vector machine based on preoperative multiparametric MR imaging of prostate cancer at 3T.
P478volume2014

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cites work (P2860)
Q91965108A Hierarchical Machine Learning Model to Discover Gleason Grade-Specific Biomarkers in Prostate Cancer
Q92167793PROSTATEx Challenges for computerized classification of prostate lesions from multiparametric magnetic resonance images
Q99419094Radiologist-like artificial intelligence for grade group prediction of radical prostatectomy for reducing upgrading and downgrading from biopsy
Q50322193The impact of computed high b-value images on the diagnostic accuracy of DWI for prostate cancer: A receiver operating characteristics analysis

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