AIMC Topic: Deep Learning

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Proposing a novel deep network for detecting COVID-19 based on chest images.

Scientific reports
The rapid outbreak of coronavirus threatens humans' life all around the world. Due to the insufficient diagnostic infrastructures, developing an accurate, efficient, inexpensive, and quick diagnostic tool is of great importance. To date, researchers ...

Resting-state electroencephalography based deep-learning for the detection of Parkinson's disease.

PloS one
Parkinson's disease (PD) is one of the most serious and challenging neurodegenerative disorders to diagnose. Clinical diagnosis on observing motor symptoms is the gold standard, yet by this point nerve cells are degenerated resulting in a lower effic...

Concordance rate of radiologists and a commercialized deep-learning solution for chest X-ray: Real-world experience with a multicenter health screening cohort.

PloS one
PURPOSE: Lunit INSIGHT CXR (Lunit) is a commercially available deep-learning algorithm-based decision support system for chest radiography (CXR). This retrospective study aimed to evaluate the concordance rate of radiologists and Lunit for thoracic a...

Identification of new putative inhibitors of 3-dehydroshikimate dehydratase from a combination of ligand- and structure-based and deep learning approaches.

Journal of biomolecular structure & dynamics
The development of new drugs against is an essential strategy for fighting drug resistance. Although 3-dehydroquinate dehydratase (MtDHQ) is known to be a highly relevant target for , current research shows new putative inhibitors of MtDHQ selected ...

MIXTURE of human expertise and deep learning-developing an explainable model for predicting pathological diagnosis and survival in patients with interstitial lung disease.

Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc
Interstitial pneumonia is a heterogeneous disease with a progressive course and poor prognosis, at times even worse than those in the main cancer types. Histopathological examination is crucial for its diagnosis and estimation of prognosis. However, ...

Radiation Dose Reduction for 80-kVp Pediatric CT Using Deep Learning-Based Reconstruction: A Clinical and Phantom Study.

AJR. American journal of roentgenology
Deep learning-based reconstruction (DLR) may facilitate CT radiation dose reduction, but a paucity of literature has compared lower-dose DLR images with standard-dose iterative reconstruction (IR) images or explored application of DLR to low-tube-vo...

Diagnostic performance of deep learning algorithm for analysis of computed tomography myocardial perfusion.

European journal of nuclear medicine and molecular imaging
PURPOSE: To evaluate the diagnostic accuracy of a deep learning (DL) algorithm predicting hemodynamically significant coronary artery disease (CAD) by using a rest dataset of myocardial computed tomography perfusion (CTP) as compared to invasive eval...

Forecasting COVID-19 new cases using deep learning methods.

Computers in biology and medicine
After nearly two years since the first identification of SARS-CoV-2 virus, the surge in cases because of virus mutations is a cause of grave public health concern across the globe. As a result of this health crisis, predicting the transmission patter...

Exploring the Effects of Ionic Defects on the Stability of CsPbI with a Deep Learning Potential.

Chemphyschem : a European journal of chemical physics and physical chemistry
Inorganic metal halide perovskites, such as CsPbI , have recently drawn extensive attention due to their excellent optical properties and high photoelectric efficiencies. However, the structural instability originating from inherent ionic defects lea...