AIMC Topic: Deep Learning

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Compensating the cell-induced light scattering effect in light-based bioprinting using deep learning.

Biofabrication
Digital light processing (DLP)-based three-dimensional (3D) printing technology has the advantages of speed and precision comparing with other 3D printing technologies like extrusion-based 3D printing. Therefore, it is a promising biomaterial fabrica...

A machine learning pipeline for classification of cetacean echolocation clicks in large underwater acoustic datasets.

PLoS computational biology
Machine learning algorithms, including recent advances in deep learning, are promising for tools for detection and classification of broadband high frequency signals in passive acoustic recordings. However, these methods are generally data-hungry and...

Deep Learning-Based Approach to Automatically Assess Coronary Distensibility Following Kawasaki Disease.

Pediatric cardiology
Kawasaki disease is an acute vasculitis affecting children, which can lead to coronary artery (CA) aneurysms. Optical coherence tomography (OCT) has identified CA wall damage in KD patients, but it is unclear if these findings correlate with any dist...

DI++: A deep learning system for patient condition identification in clinical notes.

Artificial intelligence in medicine
Accurately recording a patient's medical conditions in an EHR system is the basis of effectively documenting patient health status, coding for billing, and supporting data-driven clinical decision making. However, patient conditions are often not ful...

Development and Practical Implementation of a Deep Learning-Based Pipeline for Automated Pre- and Postoperative Glioma Segmentation.

AJNR. American journal of neuroradiology
BACKGROUND AND PURPOSE: Quantitative volumetric segmentation of gliomas has important implications for diagnosis, treatment, and prognosis. We present a deep-learning model that accommodates automated preoperative and postoperative glioma segmentatio...

GroningenNet: Deep Learning for Low-Magnitude Earthquake Detection on a Multi-Level Sensor Network.

Sensors (Basel, Switzerland)
Automatic detection of low-magnitude earthquakes has become an increasingly important research topic in recent years due to a sharp increase in induced seismicity around the globe. The detection of low-magnitude seismic events is essential for micros...

BreakNet: detecting deletions using long reads and a deep learning approach.

BMC bioinformatics
BACKGROUND: Structural variations (SVs) occupy a prominent position in human genetic diversity, and deletions form an important type of SV that has been suggested to be associated with genetic diseases. Although various deletion calling methods based...

Deep learning-based 3Ddose reconstruction with an electronic portal imaging device for magnetic resonance-linear accelerators: a proof of concept study.

Physics in medicine and biology
To develop a novel deep learning-based 3Ddose reconstruction framework with an electronic portal imaging device (EPID) for magnetic resonance-linear accelerators (MR-LINACs).The proposed method directly back-projected 2D portal dose into 3D patient c...

Deep Learning-Based Sentiment Analysis of COVID-19 Vaccination Responses from Twitter Data.

Computational and mathematical methods in medicine
The COVID-19 pandemic has had a devastating effect on many people, creating severe anxiety, fear, and complicated feelings or emotions. After the initiation of vaccinations against coronavirus, people's feelings have become more diverse and complex. ...

An investigation into the deep learning approach in sentimental analysis using graph-based theories.

PloS one
Sentiment analysis is a branch of natural language analytics that aims to correlate what is expressed which comes normally within unstructured format with what is believed and learnt. Several attempts have tried to address this gap (i.e., Naive Bayes...