AIMC Topic: Deep Learning

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Deep learning based prediction of reversible HAT/HDAC-specific lysine acetylation.

Briefings in bioinformatics
Protein lysine acetylation regulation is an important molecular mechanism for regulating cellular processes and plays critical physiological and pathological roles in cancers and diseases. Although massive acetylation sites have been identified throu...

Deep learning for drug-drug interaction extraction from the literature: a review.

Briefings in bioinformatics
Drug-drug interactions (DDIs) are crucial for drug research and pharmacovigilance. These interactions may cause adverse drug effects that threaten public health and patient safety. Therefore, the DDIs extraction from biomedical literature has been wi...

DeepSVM-fold: protein fold recognition by combining support vector machines and pairwise sequence similarity scores generated by deep learning networks.

Briefings in bioinformatics
Protein fold recognition is critical for studying the structures and functions of proteins. The existing protein fold recognition approaches failed to efficiently calculate the pairwise sequence similarity scores of the proteins in the same fold shar...

Geographic Distribution of US Cohorts Used to Train Deep Learning Algorithms.

JAMA
This study describes the US geographic distribution of patient cohorts used to train deep learning algorithms in published radiology, ophthalmology, dermatology, pathology, gastroenterology, and cardiology machine learning articles published in 2015-...

Brain tumor classification in MRI image using convolutional neural network.

Mathematical biosciences and engineering : MBE
Brain tumor is a severe cancer disease caused by uncontrollable and abnormal partitioning of cells. Recent progress in the field of deep learning has helped the health industry in Medical Imaging for Medical Diagnostic of many diseases. For Visual le...

Deep learning-based, computer-aided classifier developed with dermoscopic images shows comparable performance to 164 dermatologists in cutaneous disease diagnosis in the Chinese population.

Chinese medical journal
BACKGROUND: Diagnoses of Skin diseases are frequently delayed in China due to lack of dermatologists. A deep learning-based diagnosis supporting system can facilitate pre-screening patients to prioritize dermatologists' efforts. We aimed to evaluate ...

A natural language processing approach based on embedding deep learning from heterogeneous compounds for quantitative structure-activity relationship modeling.

Chemical biology & drug design
Over the past decade, rapid development in biological and chemical technologies such as high-throughput screening, parallel synthesis, has been significantly increased the amount of data, which requires the creation and the integration of new analyti...