AIMC Topic: Deep Learning

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CProMG: controllable protein-oriented molecule generation with desired binding affinity and drug-like properties.

Bioinformatics (Oxford, England)
MOTIVATION: Deep learning-based molecule generation becomes a new paradigm of de novo molecule design since it enables fast and directional exploration in the vast chemical space. However, it is still an open issue to generate molecules, which bind t...

PPAD: a deep learning architecture to predict progression of Alzheimer's disease.

Bioinformatics (Oxford, England)
MOTIVATION: Alzheimer's disease (AD) is a neurodegenerative disease that affects millions of people worldwide. Mild cognitive impairment (MCI) is an intermediary stage between cognitively normal state and AD. Not all people who have MCI convert to AD...

Deep learning automation of MEST-C classification in IgA nephropathy.

Nephrology, dialysis, transplantation : official publication of the European Dialysis and Transplant Association - European Renal Association
BACKGROUND: Although the MEST-C classification is among the best prognostic tools in immunoglobulin A nephropathy (IgAN), it has a wide interobserver variability between specialized pathologists and others. Therefore we trained and evaluated a tool u...

Optical Disc Segmentation from Retinal Fundus Images Using Deep Learning.

Studies in health technology and informatics
The optical disc in the human retina can reveal important information about a person's health and well-being. We propose a deep learning-based approach to automatically identify the region in human retinal images that corresponds to the optical disc....

A Deep Learning-Based Approach Towards Simultaneous Localization of Optic Disc and Fovea from Retinal Fundus Images.

Studies in health technology and informatics
In this work, we propose a multi-task learning-based approach towards the localization of optic disc and fovea from human retinal fundus images using a deep learning-based approach. Formulating the task as an image-based regression problem, we propos...

Deep Learning in Colorectal Cancer Classification: A Scoping Review.

Studies in health technology and informatics
Colorectal cancer (CRC) is one of the most common cancers worldwide, and its diagnosis and classification remain challenging for pathologists and imaging specialists. The use of artificial intelligence (AI) technology, specifically deep learning, has...

A Deep Learning Model for Classifying Histological Types of Colorectal Polyps.

Studies in health technology and informatics
In this study a deep learning architecture based on a convolutional neural network has been evaluated for the classification of white light images of colorectal polyps acquired during the process of a colonoscopy, to estimate the accuracy of the opti...

Deep Learning Framework for Categorical Emotional States Assessment Using Electrodermal Activity Signals.

Studies in health technology and informatics
In this study, we attempted to classify categorical emotional states using Electrodermal Activity (EDA) signals and a configurable Convolutional Neural Network (cCNN). The EDA signals from the publicly available, Continuously Annotated Signals of Emo...

[Deep learning-based dose prediction in radiotherapy planning for head and neck cancer].

Nan fang yi ke da xue xue bao = Journal of Southern Medical University
OBJECTIVE: To propose an deep learning-based algorithm for automatic prediction of dose distribution in radiotherapy planning for head and neck cancer.