AIMC Topic: Deep Learning

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DNAscent v2: detecting replication forks in nanopore sequencing data with deep learning.

BMC genomics
BACKGROUND: Measuring DNA replication dynamics with high throughput and single-molecule resolution is critical for understanding both the basic biology behind how cells replicate their DNA and how DNA replication can be used as a therapeutic target f...

Benefits of deep learning classification of continuous noninvasive brain-computer interface control.

Journal of neural engineering
. Noninvasive brain-computer interfaces (BCIs) assist paralyzed patients by providing access to the world without requiring surgical intervention. Prior work has suggested that EEG motor imagery based BCI can benefit from increased decoding accuracy ...

No-Reference Screen Content Image Quality Assessment With Unsupervised Domain Adaptation.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
In this paper, we quest the capability of transferring the quality of natural scene images to the images that are not acquired by optical cameras (e.g., screen content images, SCIs), rooted in the widely accepted view that the human visual system has...

Deep learning-based identification of acute ischemic core and deficit from non-contrast CT and CTA.

Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism
The accurate identification of irreversible infarction and salvageable tissue is important in planning the treatments for acute ischemic stroke (AIS) patients. Computed tomographic perfusion (CTP) can be used to evaluate the ischemic core and deficit...

Deep learning connects DNA traces to transcription to reveal predictive features beyond enhancer-promoter contact.

Nature communications
Chromatin architecture plays an important role in gene regulation. Recent advances in super-resolution microscopy have made it possible to measure chromatin 3D structure and transcription in thousands of single cells. However, leveraging these comple...

Implementation of deep learning-based auto-segmentation for radiotherapy planning structures: a workflow study at two cancer centers.

Radiation oncology (London, England)
PURPOSE: We recently described the validation of deep learning-based auto-segmented contour (DC) models for organs at risk (OAR) and clinical target volumes (CTV). In this study, we evaluate the performance of implemented DC models in the clinical ra...

Deep Learning on Chest X-ray Images to Detect and Evaluate Pneumonia Cases at the Era of COVID-19.

Journal of medical systems
Coronavirus disease 2019 (COVID-19) is an infectious disease with first symptoms similar to the flu. COVID-19 appeared first in China and very quickly spreads to the rest of the world, causing then the 2019-20 coronavirus pandemic. In many cases, thi...

Deep Learning Application for Vocal Fold Disease Prediction Through Voice Recognition: Preliminary Development Study.

Journal of medical Internet research
BACKGROUND: Dysphonia influences the quality of life by interfering with communication. However, a laryngoscopic examination is expensive and not readily accessible in primary care units. Experienced laryngologists are required to achieve an accurate...

In silico prediction of drug-induced ototoxicity using machine learning and deep learning methods.

Chemical biology & drug design
Drug-induced ototoxicity has become a serious global problem, because of leading to deafness in hundreds of thousands of people every year. It always results from exposure to drugs or environmental chemicals that cause the impairment and degeneration...