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Neoplasm Grading

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[Prostate cancer pathologic features in men ≤55 years treated with robot assisted radical prostatectomy.].

Archivos espanoles de urologia
OBJECTIVE: Among western males, prostate cancer is the most frequent oncological disease. Since the widespread of PSA, diagnoses in younger adults is increasing. The aim of this study is to analyze pathological features and biochemical recurrence eve...

Automated Gleason grading of prostate cancer using transfer learning from general-purpose deep-learning networks.

Romanian journal of morphology and embryology = Revue roumaine de morphologie et embryologie
Two deep-learning algorithms designed to classify images according to the Gleason grading system that used transfer learning from two well-known general-purpose image classification networks (AlexNet and GoogleNet) were trained on Hematoxylin-Eosin h...

Evaluation of Prognosis in Nasopharyngeal Cancer Using Machine Learning.

Technology in cancer research & treatment
BACKGROUND AND AIM: Although the prognosis of nasopharyngeal cancer largely depends on a classification based on the tumor-lymph node metastasis staging system, patients at the same stage may have different clinical outcomes. This study aimed to eval...

Radiomics MRI Phenotyping with Machine Learning to Predict the Grade of Lower-Grade Gliomas: A Study Focused on Nonenhancing Tumors.

Korean journal of radiology
OBJECTIVE: To assess whether radiomics features derived from multiparametric MRI can predict the tumor grade of lower-grade gliomas (LGGs; World Health Organization grade II and grade III) and the nonenhancing LGG subgroup.

Hybrid Unified Deep Learning Network for Highly Precise Gleason Grading of Prostate Cancer.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Prostate cancer is one of the leading causes of death around the world. The manual Gleason grading of prostate cancer after histological analysis of stained tissue slides is rigorous, time-consuming and also suffers from subjectivity among experts. I...

Automating the Capture of Structured Pathology Data for Prostate Cancer Clinical Care and Research.

JCO clinical cancer informatics
PURPOSE: Cancer pathology findings are critical for many aspects of care but are often locked away as unstructured free text. Our objective was to develop a natural language processing (NLP) system to extract prostate pathology details from postopera...

A novel machine learning-derived decision tree including uPA/PAI-1 for breast cancer care.

Clinical chemistry and laboratory medicine
Background uPA and PAI-1 are breast cancer biomarkers that evaluate the benefit of chemotherapy (CT) for HER2-negative, estrogen receptor-positive, low or intermediate grade patients. Our objectives were to observe clinical routine use of uPA/PAI-1 a...

Artificial intelligence at the intersection of pathology and radiology in prostate cancer.

Diagnostic and interventional radiology (Ankara, Turkey)
Pathologic grading plays a key role in prostate cancer risk stratification and treatment selection, traditionally assessed from systemic core needle biopsies sampled throughout the prostate gland. Multiparametric magnetic resonance imaging (mpMRI) ha...

Prediction of ISUP grading of clear cell renal cell carcinoma using support vector machine model based on CT images.

Medicine
BACKGROUND: To explore whether radiomics combined with computed tomography (CT) images can be used to establish a model for differentiating high grade (International Society of Urological Pathology [ISUP] grade III-IV) from low-grade (ISUP I-II) clea...