AIMC Topic: Neural Networks, Computer

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Fully automatic multi-organ segmentation for head and neck cancer radiotherapy using shape representation model constrained fully convolutional neural networks.

Medical physics
PURPOSE: Intensity modulated radiation therapy (IMRT) is commonly employed for treating head and neck (H&N) cancer with uniform tumor dose and conformal critical organ sparing. Accurate delineation of organs-at-risk (OARs) on H&N CT images is thus es...

Multi-stage optimization of a deep model: A case study on ground motion modeling.

PloS one
In this study, a multi-stage optimization procedure is proposed to develop deep neural network models which results in a powerful deep learning pipeline called intelligent deep learning (iDeepLe). The proposed pipeline is then evaluated by a challeng...

Factorization machines and deep views-based co-training for improving answer quality prediction in online health expert question-answering services.

Journal of biomedical informatics
In online health expert question-answering (HQA) services, it is significant to automatically determine the quality of the answers. There are two prominent challenges in this task. First, the answers are usually written in short text, which makes it ...

CNN as model observer in a liver lesion detection task for x-ray computed tomography: A phantom study.

Medical physics
PURPOSE: The purpose of this study was the evaluation of anthropomorphic model observers trained with neural networks for the prediction of a human observer's performance.

A Hybrid Deep Learning Model for Predicting Protein Hydroxylation Sites.

International journal of molecular sciences
Protein hydroxylation is one type of post-translational modifications (PTMs) playing critical roles in human diseases. It is known that protein sequence contains many uncharacterized residues of proline and lysine. The question that needs to be answe...

Deep Learning in Drug Discovery and Medicine; Scratching the Surface.

Molecules (Basel, Switzerland)
The practice of medicine is ever evolving. Diagnosing disease, which is often the first step in a cure, has seen a sea change from the discerning hands of the neighborhood physician to the use of sophisticated machines to use of information gleaned f...

Detection of masses in mammograms using a one-stage object detector based on a deep convolutional neural network.

PloS one
Several computer aided diagnosis (CAD) systems have been developed for mammography. They are widely used in certain countries such as the U.S. where mammography studies are conducted more frequently; however, they are not yet globally employed for cl...

Memetic Search Optimization Along with Genetic Scale Recurrent Neural Network for Predictive Rate of Implant Treatment.

Journal of medical systems
Implant treatment is one of the most important surgical processes in teeth which reduces the difficulties in teeth by providing the interface between bone and jaw. The established implant treatment used to support the denture, bridge and teeth crown....

A document level neural model integrated domain knowledge for chemical-induced disease relations.

BMC bioinformatics
BACKGROUND: The effective combination of texts and knowledge may improve performances of natural language processing tasks. For the recognition of chemical-induced disease (CID) relations which may span sentence boundaries in an article, although exi...