AIMC Topic: Deep Learning

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A Web-Based Protocol for Interprotein Contact Prediction by Deep Learning.

Methods in molecular biology (Clifton, N.J.)
Identifying residue-residue contacts in protein-protein interactions or complex is crucial for understanding protein and cell functions. DCA (direct-coupling analysis) methods shed some light on this, but they need many sequence homologs to yield acc...

Recent and Upcoming Technological Developments in Computed Tomography: High Speed, Low Dose, Deep Learning, Multienergy.

Investigative radiology
The advent of computed tomography (CT) has revolutionized radiology, and this revolution is still going on. Starting as a pure head scanner, modern CT systems are now able to perform whole-body examinations within a couple of seconds in isotropic res...

Deep Learning in Automated Region Proposal and Diagnosis of Chronic Otitis Media Based on Computed Tomography.

Ear and hearing
OBJECTIVES: The purpose of this study was to develop a deep-learning framework for the diagnosis of chronic otitis media (COM) based on temporal bone computed tomography (CT) scans.

Deep Learning in the Study of Protein-Related Interactions.

Protein and peptide letters
Protein-related interaction prediction is critical to understanding life processes, biological functions, and mechanisms of drug action. Experimental methods used to determine proteinrelated interactions have always been costly and inefficient. In re...

Identifying relations of medications with adverse drug events using recurrent convolutional neural networks and gradient boosting.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: To develop a natural language processing system that identifies relations of medications with adverse drug events from clinical narratives. This project is part of the 2018 n2c2 challenge.

Quantifying the Association Between Psychotherapy Content and Clinical Outcomes Using Deep Learning.

JAMA psychiatry
IMPORTANCE: Compared with the treatment of physical conditions, the quality of care of mental health disorders remains poor and the rate of improvement in treatment is slow, a primary reason being the lack of objective and systematic methods for meas...

Adverse drug events and medication relation extraction in electronic health records with ensemble deep learning methods.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Identification of drugs, associated medication entities, and interactions among them are crucial to prevent unwanted effects of drug therapy, known as adverse drug events. This article describes our participation to the n2c2 shared-task in...

DeePaC: predicting pathogenic potential of novel DNA with reverse-complement neural networks.

Bioinformatics (Oxford, England)
MOTIVATION: We expect novel pathogens to arise due to their fast-paced evolution, and new species to be discovered thanks to advances in DNA sequencing and metagenomics. Moreover, recent developments in synthetic biology raise concerns that some stra...

circDeep: deep learning approach for circular RNA classification from other long non-coding RNA.

Bioinformatics (Oxford, England)
MOTIVATION: Over the past two decades, a circular form of RNA (circular RNA), produced through alternative splicing, has become the focus of scientific studies due to its major role as a microRNA (miRNA) activity modulator and its association with va...

Deep learning on chaos game representation for proteins.

Bioinformatics (Oxford, England)
MOTIVATION: Classification of protein sequences is one big task in bioinformatics and has many applications. Different machine learning methods exist and are applied on these problems, such as support vector machines (SVM), random forests (RF) and ne...