AIMC Topic: Humans

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Classification Criteria For Pars Planitis.

American journal of ophthalmology
PURPOSE: To determine classification criteria for pars planitis.

Classification Criteria for Spondyloarthritis/HLA-B27-Associated Anterior Uveitis.

American journal of ophthalmology
PURPOSE: The purpose of this study was to determine classification criteria for spondyloarthritis/HLA-B27-associated anterior uveitis DESIGN: Machine learning of cases with spondyloarthritis/HLA-B27-associated anterior uveitis and 8 other anterior uv...

A controlled human infection model of Streptococcus pyogenes pharyngitis (CHIVAS-M75): an observational, dose-finding study.

The Lancet. Microbe
BACKGROUND: Streptococcus pyogenes is a leading cause of infection-related morbidity and mortality. A reinvigorated vaccine development effort calls for new clinically relevant human S pyogenes experimental infection models to support proof of concep...

Deep learning reconstruction of digital breast tomosynthesis images for accurate breast density and patient-specific radiation dose estimation.

Medical image analysis
The two-dimensional nature of mammography makes estimation of the overall breast density challenging, and estimation of the true patient-specific radiation dose impossible. Digital breast tomosynthesis (DBT), a pseudo-3D technique, is now commonly us...

A deep learning based multiscale approach to segment the areas of interest in whole slide images.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
This paper addresses the problem of liver cancer segmentation in Whole Slide Images (WSIs). We propose a multi-scale image processing method based on an automatic end-to-end deep neural network algorithm for the segmentation of cancerous areas. A sev...

DenseCapsNet: Detection of COVID-19 from X-ray images using a capsule neural network.

Computers in biology and medicine
At present, the global pandemic as it relates to novel coronavirus pneumonia is still a very difficult situation. Due to the recent outbreak of novel coronavirus pneumonia, novel chest X-ray (CXR) images that can be used for deep learning analysis ar...

CovidXrayNet: Optimizing data augmentation and CNN hyperparameters for improved COVID-19 detection from CXR.

Computers in biology and medicine
To mitigate the spread of the current coronavirus disease 2019 (COVID-19) pandemic, it is crucial to have an effective screening of infected patients to be isolated and treated. Chest X-Ray (CXR) radiological imaging coupled with Artificial Intellige...

Optimization of therapeutic antibodies by predicting antigen specificity from antibody sequence via deep learning.

Nature biomedical engineering
The optimization of therapeutic antibodies is time-intensive and resource-demanding, largely because of the low-throughput screening of full-length antibodies (approximately 1 × 10 variants) expressed in mammalian cells, which typically results in fe...

A deep-learning pipeline for the diagnosis and discrimination of viral, non-viral and COVID-19 pneumonia from chest X-ray images.

Nature biomedical engineering
Common lung diseases are first diagnosed using chest X-rays. Here, we show that a fully automated deep-learning pipeline for the standardization of chest X-ray images, for the visualization of lesions and for disease diagnosis can identify viral pneu...