AIMC Topic:
Prostatic Neoplasms
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Agreement of two pre-trained deep-learning neural networks built with transfer learning with six pathologists on 6000 patches of prostate cancer from Gleason2019 Challenge.
Romanian journal of morphology and embryology = Revue roumaine de morphologie et embryologie
Jan 1, 2020
INTRODUCTION: While the visual inspection of histopathology images by expert pathologists remains the golden standard method for grading of prostate cancer the quest for developing automated algorithms for the job is set and deep-learning techniques ...
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
Jan 1, 2020
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...
Effect of pelvimetric diameters on success of surgery in patients submitted to robot-assisted perineal radical prostatectomy.
International braz j urol : official journal of the Brazilian Society of Urology
Jan 1, 2020
OBJECTIVE: Minimally invasive techniques are used increasingly by virtue of advancements in technology. Surgery for prostate cancer, which has high morbidity, is performed with an increasing momentum based on the successful oncological and functional...
[Artificial intelligence and radiomics in MRI-based prostate diagnostics].
Der Radiologe
Jan 1, 2020
CLINICAL/METHODICAL ISSUE: In view of the diagnostic complexity and the large number of examinations, modern radiology is challenged to identify clinically significant prostate cancer (PCa) with high sensitivity and specificity. Meanwhile overdiagnos...
Robot-assisted radical prostatectomy vs. open radical prostatectomy: latest evidences on perioperative, functional and oncological outcomes.
Current opinion in urology
Jan 1, 2020
PURPOSE OF REVIEW: Despite increasing use of robotic surgery for radical prostatectomy, the benefit of robotic over open approach on different postoperative outcomes is still under debate. The present review aimed to provide a framework on the latest...
Hunting for New Drugs with AI.
Nature
Dec 1, 2019
United States Food and Drug Administration
Drug Industry
Cytochrome P-450 Enzyme System
Drug Approval
Cytochrome P-450 Enzyme Inhibitors
Parkinson Disease
Prostatic Neoplasms
Drug-Related Side Effects and Adverse Reactions
Drug Discovery
United States
Humans
Artificial Intelligence
Machine Learning
Male
Drug Design
A convolutional neural network approach for IMRT dose distribution prediction in prostate cancer patients.
Journal of radiation research
Oct 23, 2019
The purpose of the study was to compare a 3D convolutional neural network (CNN) with the conventional machine learning method for predicting intensity-modulated radiation therapy (IMRT) dose distribution using only contours in prostate cancer. In thi...
A Deep Learning-Based Approach for the Detection and Localization of Prostate Cancer in T2 Magnetic Resonance Images.
Journal of digital imaging
Oct 1, 2019
We address the problem of prostate lesion detection, localization, and segmentation in T2W magnetic resonance (MR) images. We train a deep convolutional encoder-decoder architecture to simultaneously segment the prostate, its anatomical structure, an...
Identification of caveolin-1 domain signatures via machine learning and graphlet analysis of single-molecule super-resolution data.
Bioinformatics (Oxford, England)
Sep 15, 2019
MOTIVATION: Network analysis and unsupervised machine learning processing of single-molecule localization microscopy of caveolin-1 (Cav1) antibody labeling of prostate cancer cells identified biosignatures and structures for caveolae and three distin...
Radiology-Pathology Correlation to Facilitate Peer Learning: An Overview Including Recent Artificial Intelligence Methods.
Journal of the American College of Radiology : JACR
Sep 1, 2019
Correlation of pathology reports with radiology examinations has long been of interest to radiologists and helps to facilitate peer learning. Such correlation also helps meet regulatory requirements, ensures quality, and supports multidisciplinary co...
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