PD11-01 AUTOMATED HISTOPATHOLOGIC DIAGNOSIS AND GLEASON GRADING OF PROSTATE BIOPSIES WITH MACHINE LEARNING

Automated Prostate Cancer Diagnosis and Gleason Grading of Tissue Microarrays

We present the results on the development of an automated system for prostate cancer diagnosis and Gleason grading. Images of representative areas of the original Hematoxylin-and-Eosin (H&E)-stained tissue retrieved from each patient, either from a tissue microarray (TMA) core or whole section, were captured and analyzed. The image sets consisted of 367 and 268 color images for the diagnosis an...

Automatic Gleason grading of prostate cancer using quantitative phase imaging and machine learning.

We present an approach for automatic diagnosis of tissue biopsies. Our methodology consists of a quantitative phase imaging tissue scanner and machine learning algorithms to process these data. We illustrate the performance by automatic Gleason grading of prostate specimens. The imaging system operates on the principle of interferometry and, as a result, reports on the nanoscale architecture of...

Gleason grading of prostate cancer. Contemporary approach.

Automated Essay Grading Using Machine Learning

The project aims to build an automated essay scoring system using a data set of ≈13000 essays from kaggle.com. These essays were divided into 8 di erent sets based on context. We extracted features such as total word count per essay, sentence count, number of long words, part of speech counts etc from the training set essays. We used a linear regression model to learn from these features and ge...

Interobserver variability in Gleason histological grading of prostate cancer.

OBJECTIVE The aims of this study were to evaluate the reproducibility of the Gleason grading system and to compare its interobserver variability with the novel Gleason grade grouping proposal using a large sample volume. MATERIALS AND METHODS In total, 407 pathology slides of prostate needle biopsies from 34 consecutive patients with prostate cancer were re-evaluated. The International Societ...