AIMC Topic: Biopsy

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Predicting Advanced Prostate Cancer from Modeling Early Indications in Biopsy and Prostatectomy Samples via Transductive Semi-Supervised Survival Analysis.

BioMed research international
Prostate cancer is the most prevalent form of cancer and the second most common cause of cancer deaths among men in the United States. Accurate prognosis is important as it is the principal factor in determining the treatment plan. Prostate cancer is...

Optical classification of neoplastic colorectal polyps - a computer-assisted approach (the COACH study).

Scandinavian journal of gastroenterology
BACKGROUND AND AIMS: Clinical data suggest that the quality of optical diagnoses of colorectal polyps differs markedly among endoscopists. The aim of this study was to develop a computer program that was able to differentiate neoplastic from non-neop...

Support Vector Machines and logistic regression to predict temporal artery biopsy outcomes.

Canadian journal of ophthalmology. Journal canadien d'ophtalmologie
OBJECTIVE: Support vector machines (SVM) is a newer statistical method that has been reported to be advantageous to traditional logistic regression for clinical classification. We determine if SVM can better predict the results of temporal artery bio...

Classification of lung adenocarcinoma transcriptome subtypes from pathological images using deep convolutional networks.

International journal of computer assisted radiology and surgery
PURPOSE: Convolutional neural networks have become rapidly popular for image recognition and image analysis because of its powerful potential. In this paper, we developed a method for classifying subtypes of lung adenocarcinoma from pathological imag...

Lupus nephritis pathology prediction with clinical indices.

Scientific reports
Effective treatment of lupus nephritis and assessment of patient prognosis depend on accurate pathological classification and careful use of acute and chronic pathological indices. Renal biopsy can provide most reliable predicting power. However, cli...

Comparison of Transferred Deep Neural Networks in Ultrasonic Breast Masses Discrimination.

BioMed research international
This research aims to address the problem of discriminating benign cysts from malignant masses in breast ultrasound (BUS) images based on Convolutional Neural Networks (CNNs). The biopsy-proven benchmarking dataset was built from 1422 patient cases c...

Using deep convolutional neural networks to identify and classify tumor-associated stroma in diagnostic breast biopsies.

Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc
The breast stromal microenvironment is a pivotal factor in breast cancer development, growth and metastases. Although pathologists often detect morphologic changes in stroma by light microscopy, visual classification of such changes is subjective and...

Deep learning Radiomics of shear wave elastography significantly improved diagnostic performance for assessing liver fibrosis in chronic hepatitis B: a prospective multicentre study.

Gut
OBJECTIVE: We aimed to evaluate the performance of the newly developed deep learning Radiomics of elastography (DLRE) for assessing liver fibrosis stages. DLRE adopts the radiomic strategy for quantitative analysis of the heterogeneity in two-dimensi...