Pages that link to "Q45392561"

The following pages link to Systems pathology approach for the prediction of prostate cancer progression after radical prostatectomy (Q45392561):

Displaying 37 items.

• Molecular preservation by extraction and fixation, mPREF: a method for small molecule biomarker analysis and histology on exactly the same tissue (Q31043717) (← links)
• Postoperative systems models more accurately predict risk of significant disease progression than standard risk groups and a 10‐year postoperative nomogram: potential impact on the receipt of adjuvant therapy after surgery (Q33669456) (← links)
• Relationship between SRD5A2 rs9282858 polymorphism and the susceptibility of prostate cancer: A meta-analysis based on 20 publications (Q33672581) (← links)
• High-throughput detection of prostate cancer in histological sections using probabilistic pairwise Markov models (Q34047679) (← links)
• Dual role of FoxA1 in androgen receptor binding to chromatin, androgen signalling and prostate cancer (Q34216102) (← links)
• A clinicogenetic model to predict lymph node invasion by use of genome-based biomarkers from exome arrays in prostate cancer patients (Q35074949) (← links)
• Novel Gene Expression Signature Predictive of Clinical Recurrence After Radical Prostatectomy in Early Stage Prostate Cancer Patients (Q36043833) (← links)
• Evaluating Prostate Cancer Using Fractional Tissue Composition of Radical Prostatectomy Specimens and Pre-Operative Diffusional Kurtosis Magnetic Resonance Imaging (Q36088325) (← links)
• Cost-Effectiveness of a Biopsy-Based 8-Protein Prostate Cancer Prognostic Assay to Optimize Treatment Decision Making in Gleason 3 3 and 3 4 Early Stage Prostate Cancer (Q36371617) (← links)
• Computational pathology of pre-treatment biopsies identifies lymphocyte density as a predictor of response to neoadjuvant chemotherapy in breast cancer. (Q36584124) (← links)
• Astronomical algorithms for automated analysis of tissue protein expression in breast cancer (Q36671817) (← links)
• Quantitative Time-Resolved Fluorescence Imaging of Androgen Receptor and Prostate-Specific Antigen in Prostate Tissue Sections (Q36852430) (← links)
• Comparison of models to predict clinical failure after radical prostatectomy (Q37339685) (← links)
• Systems pathology: a paradigm shift in the practice of diagnostic and predictive pathology (Q37526803) (← links)
• Additional therapy for high-risk prostate cancer treated with surgery: what is the evidence? (Q37546041) (← links)
• Radiolabeled 5-iodo-3'-O-(17beta-succinyl-5alpha-androstan-3-one)-2'-deoxyuridine and its 5'-monophosphate for imaging and therapy of androgen receptor-positive cancers: synthesis and biological evaluation (Q37616008) (← links)
• Systems pathology: A critical review (Q37969429) (← links)
• Overcoming tumor heterogeneity in the molecular diagnosis of urological cancers (Q38261250) (← links)
• PathGrid: a service-orientated architecture for microscopy image analysis (Q38428392) (← links)
• A four gene signature predictive of recurrent prostate cancer (Q38783018) (← links)
• Factors Implicated in Radiation Therapy Failure and Radiosensitization of Prostate Cancer (Q38807901) (← links)
• Cross-species regulatory network analysis identifies a synergistic interaction between FOXM1 and CENPF that drives prostate cancer malignancy (Q38995507) (← links)
• Implementation of a Precision Pathology Program Focused on Oncology-Based Prognostic and Predictive Outcomes. (Q39045171) (← links)
• Histone H1 expression in human prostate cancer tissues and cell lines. (Q39412667) (← links)
• Genome-wide detection of allelic genetic variation to predict biochemical recurrence after radical prostatectomy among prostate cancer patients using an exome SNP chip (Q41236835) (← links)
• Molecular processes leading to aberrant androgen receptor signaling and castration resistance in prostate cancer (Q41886996) (← links)
• A systems‐based modelling approach using transurethral resection of the prostate (TURP) specimens yielded incremental prognostic significance to Gleason when predicting long‐term outcome in men with localized prostate cancer (Q42491097) (← links)
• Automated quantitative multiplex immunofluorescence in situ imaging identifies phospho-S6 and phospho-PRAS40 as predictive protein biomarkers for prostate cancer lethality. (Q42754619) (← links)
• Independent Diagnostic and Post-Treatment Prognostic Models for Prostate Cancer Demonstrate Significant Correlation with Disease Progression End Points (Q43454370) (← links)
• Predicting and replacing the pathological Gleason grade with automated gland ring morphometric features from immunofluorescent prostate cancer images (Q47919326) (← links)
• Quantification of large scale DNA organization for predicting prostate cancer recurrence (Q48516686) (← links)
• Systematic analysis of breast cancer morphology uncovers stromal features associated with survival (Q50994600) (← links)
• Early-Stage Event Prediction for Longitudinal Data (Q58312480) (← links)
• Predicting Advanced Prostate Cancer from Modeling Early Indications in Biopsy and Prostatectomy Samples via Transductive Semi-Supervised Survival Analysis (Q58695031) (← links)
• Multiple immunofluorescence assay identifies upregulation of Active β-catenin in prostate cancer (Q61805899) (← links)
• Predictive models for newly diagnosed prostate cancer patients (Q84912363) (← links)
• Development and validation of a novel automated Gleason grade and molecular profile that define a highly predictive prostate cancer progression algorithm-based test (Q90825986) (← links)