AIMC Topic: Neoplasm Grading

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Pathomics in urology.

Current opinion in urology
PURPOSE OF REVIEW: Pathomics, the fusion of digitalized pathology and artificial intelligence, is currently changing the landscape of medical pathology and biologic disease classification. In this review, we give an overview of Pathomics and summariz...

An artificial intelligence algorithm for prostate cancer diagnosis in whole slide images of core needle biopsies: a blinded clinical validation and deployment study.

The Lancet. Digital health
BACKGROUND: There is high demand to develop computer-assisted diagnostic tools to evaluate prostate core needle biopsies (CNBs), but little clinical validation and a lack of clinical deployment of such tools. We report here on a blinded clinical vali...

Carcino-Net: A Deep Learning Framework for Automated Gleason Grading of Prostate Biopsies.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Gleason scoring for prostate cancer grading is a subjective examination and suffers from suboptimal interobserver and intraobserver variability. To overcome these limitations, we have developed an automated system to grade prostate biopsies. We prese...

The study of multiple diagnosis models of human prostate cancer based on Taylor database by artificial neural networks.

Journal of the Chinese Medical Association : JCMA
BACKGROUND: Prostate cancer (PCa) is the most common malignancy seen in men and the second leading cause of cancer-related death in males. The incidence and mortality associated with PCa has been rapidly increasing in China recently.

[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.