AI Medical Compendium Topic:
Prostatic Neoplasms

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A machine learning-assisted decision-support model to better identify patients with prostate cancer requiring an extended pelvic lymph node dissection.

BJU international
OBJECTIVES: To develop a machine learning (ML)-assisted model to identify candidates for extended pelvic lymph node dissection (ePLND) in prostate cancer by integrating clinical, biopsy, and precisely defined magnetic resonance imaging (MRI) findings...

Hospital readmissions after limited vs. extended lymph node dissection during open and robot-assisted radical prostatectomy.

Urologic oncology
PURPOSE: Differences exist concerning when and how to perform lymph node dissection (LND) during radical prostatectomy due to lack of high-grade evidence to its safety and efficacy. We aimed to compare readmission rates between limited and extended L...

Learning to detect lymphocytes in immunohistochemistry with deep learning.

Medical image analysis
The immune system is of critical importance in the development of cancer. The evasion of destruction by the immune system is one of the emerging hallmarks of cancer. We have built a dataset of 171,166 manually annotated CD3 and CD8 cells, which we us...

Encoder-decoder with dense dilated spatial pyramid pooling for prostate MR images segmentation.

Computer assisted surgery (Abingdon, England)
Automatic segmentation of prostate magnetic resonance (MR) images has great significance for the diagnosis and clinical application of prostate diseases. It faces enormous challenges because of the low contrast of the tissue boundary and the small ef...

Boundary-Weighted Domain Adaptive Neural Network for Prostate MR Image Segmentation.

IEEE transactions on medical imaging
Accurate segmentation of the prostate from magnetic resonance (MR) images provides useful information for prostate cancer diagnosis and treatment. However, automated prostate segmentation from 3D MR images faces several challenges. The lack of clear ...

An augmented reality microscope with real-time artificial intelligence integration for cancer diagnosis.

Nature medicine
The microscopic assessment of tissue samples is instrumental for the diagnosis and staging of cancer, and thus guides therapy. However, these assessments demonstrate considerable variability and many regions of the world lack access to trained pathol...

Machine learning applications in prostate cancer magnetic resonance imaging.

European radiology experimental
With this review, we aimed to provide a synopsis of recently proposed applications of machine learning (ML) in radiology focusing on prostate magnetic resonance imaging (MRI). After defining the difference between ML and classical rule-based algorith...

Is a Drain Needed After Robotic Radical Prostatectomy With or Without Pelvic Lymph Node Dissection? Results of a Single-Center Randomized Clinical Trial.

Journal of endourology
To investigate by means of a randomized clinical trial the safety of no drain in the pelvic cavity after robot-assisted radical prostatectomy (RARP) with or without extended pelvic lymph node dissection (ePLND). From May to December 2016, 112 conse...

Deep learning approaches using 2D and 3D convolutional neural networks for generating male pelvic synthetic computed tomography from magnetic resonance imaging.

Medical physics
PURPOSE: The improved soft tissue contrast of magnetic resonance imagingĀ (MRI) compared to computed tomography (CT) makes it a useful imaging modality for radiotherapy treatment planning. Even when MR images are acquired for treatment planning, the s...