AIMC Topic: Deep Learning

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Predicting enhancer-promoter interactions by deep learning and matching heuristic.

Briefings in bioinformatics
Enhancer-promoter interactions (EPIs) play an important role in transcriptional regulation. Recently, machine learning-based methods have been widely used in the genome-scale identification of EPIs due to their promising predictive performance. In th...

DeepHPV: a deep learning model to predict human papillomavirus integration sites.

Briefings in bioinformatics
Human papillomavirus (HPV) integrating into human genome is the main cause of cervical carcinogenesis. HPV integration selection preference shows strong dependence on local genomic environment. Due to this theory, it is possible to predict HPV integr...

Deep-DRM: a computational method for identifying disease-related metabolites based on graph deep learning approaches.

Briefings in bioinformatics
MOTIVATION: The functional changes of the genes, RNAs and proteins will eventually be reflected in the metabolic level. Increasing number of researchers have researched mechanism, biomarkers and targeted drugs by metabolites. However, compared with o...

Predicting the interaction biomolecule types for lncRNA: an ensemble deep learning approach.

Briefings in bioinformatics
Long noncoding RNAs (lncRNAs) play significant roles in various physiological and pathological processes via their interactions with biomolecules like DNA, RNA and protein. The existing in silico methods used for predicting the functions of lncRNA ma...

Deep learning and radiomics analysis for prediction of placenta invasion based on T2WI.

Mathematical biosciences and engineering : MBE
The purpose of this study was to explore whether the Nomogram, which was constructed by combining the Deep learning and Radiomic features of T2-weighted MR images with Clinical factors (NDRC), could accurately predict placenta invasion. This retrospe...

Neuroprosthesis for Decoding Speech in a Paralyzed Person with Anarthria.

The New England journal of medicine
BACKGROUND: Technology to restore the ability to communicate in paralyzed persons who cannot speak has the potential to improve autonomy and quality of life. An approach that decodes words and sentences directly from the cerebral cortical activity of...

Heuristic hyperparameter optimization of deep learning models for genomic prediction.

G3 (Bethesda, Md.)
There is a growing interest among quantitative geneticists and animal breeders in the use of deep learning (DL) for genomic prediction. However, the performance of DL is affected by hyperparameters that are typically manually set by users. These hype...

Deep-learning-based automated terminology mapping in OMOP-CDM.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Accessing medical data from multiple institutions is difficult owing to the interinstitutional diversity of vocabularies. Standardization schemes, such as the common data model, have been proposed as solutions to this problem, but such sch...

Transfer learning for mobile real-time face mask detection and localization.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Due to the COVID-19 pandemic, our daily habits have suddenly changed. Gatherings are forbidden and, even when it is possible to leave the home for health or work reasons, it is necessary to wear a face mask to reduce the possibility of con...

Extracting postmarketing adverse events from safety reports in the vaccine adverse event reporting system (VAERS) using deep learning.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Automated analysis of vaccine postmarketing surveillance narrative reports is important to understand the progression of rare but severe vaccine adverse events (AEs). This study implemented and evaluated state-of-the-art deep learning algo...