AIMC Topic: Deep Learning

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Convolutional Neural Network-Based Deep Learning Model for Predicting Differential Suicidality in Depressive Patients Using Brain Generalized q-Sampling Imaging.

The Journal of clinical psychiatry Feb 23, 2021
OBJECTIVE: Suicide is a priority health problem. Suicide assessment depends on imperfect clinician assessment with minimal ability to predict the risk of suicide. Machine learning/deep learning provides an opportunity to detect an individual at risk ...
Young Adult Adult Male Middle Aged Risk Assessment Suicide, Attempted Algorithms Brain Female Suicidal Ideation Depressive Disorder Magnetic Resonance Imaging Case-Control Studies Interview, Psychological Neuroimaging Deep Learning Humans Neural Networks, Computer
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Deep Learning Feature Extraction Approach for Hematopoietic Cancer Subtype Classification.

International journal of environmental research and public health Feb 23, 2021
Hematopoietic cancer is a malignant transformation in immune system cells. Hematopoietic cancer is characterized by the cells that are expressed, so it is usually difficult to distinguish its heterogeneities in the hematopoiesis process. Traditional ...
Support Vector Machine Hematopoietic Stem Cell Transplantation Neural Networks, Computer Algorithms Neoplasms Deep Learning
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Deep Residual Network in Network.

Computational intelligence and neuroscience Feb 23, 2021
Deep network in network (DNIN) model is an efficient instance and an important extension of the convolutional neural network (CNN) consisting of alternating convolutional layers and pooling layers. In this model, a multilayer perceptron (MLP), a nonl...
Learning Neural Networks, Computer Deep Learning Machine Learning
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Identification of RNA pseudouridine sites using deep learning approaches.

PloS one Feb 23, 2021
Pseudouridine(Ψ) is widely popular among various RNA modifications which have been confirmed to occur in rRNA, mRNA, tRNA, and nuclear/nucleolar RNA. Hence, identifying them has vital significance in academic research, drug development and gene thera...
RNA, Ribosomal Pseudouridine Computational Biology Humans RNA Animals Saccharomyces cerevisiae Deep Learning Mice
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A comparison between deep learning convolutional neural networks and radiologists in the differentiation of benign and malignant thyroid nodules on CT images.

Endokrynologia Polska Feb 23, 2021
INTRODUCTION: We designed 5 convolutional neural network (CNN) models and ensemble models to differentiate malignant and benign thyroid nodules on CT, and compared the diagnostic performance of CNN models with that of radiologists.
Humans Neural Networks, Computer Retrospective Studies Thyroid Nodule Tomography, X-Ray Computed Lung Neoplasms Deep Learning Radiologists Thyroid Neoplasms
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Reducing Contrast Agent Dose in Cardiovascular MR Angiography with Deep Learning.

Journal of magnetic resonance imaging : JMRI Feb 22, 2021
BACKGROUND: Contrast-enhanced magnetic resonance angiography (MRA) is used to assess various cardiovascular conditions. However, gadolinium-based contrast agents (GBCAs) carry a risk of dose-related adverse effects.
Magnetic Resonance Angiography Reducing Agents Imaging, Three-Dimensional Contrast Media Humans Prospective Studies Retrospective Studies Deep Learning
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Real-time monitoring of forward osmosis membrane fouling in wastewater reuse process performed with a deep learning model.

Chemosphere Feb 22, 2021
Monitoring fouling behavior for better understanding and control has recently gained increasing attention. However, there is no practical method for observing membrane fouling in real time, especially in the forward osmosis (FO) process. In this arti...
Membranes, Artificial Osmosis Wastewater Water Purification Deep Learning
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Super-resolution head and neck MRA using deep machine learning.

Magnetic resonance in medicine Feb 22, 2021
PURPOSE: To probe the feasibility of deep learning-based super-resolution (SR) reconstruction applied to nonenhanced MR angiography (MRA) of the head and neck.
Humans Neck Magnetic Resonance Angiography Machine Learning Deep Learning Imaging, Three-Dimensional
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Classification of pachychoroid on optical coherence tomography using deep learning.

Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie Feb 22, 2021
PURPOSE: Pachychoroid is characterized by dilated Haller vessels and choriocapillaris attenuation that are seen on optical coherence tomography (OCT) B-scans. This study investigated the feasibility of using deep learning (DL) models to classify pach...
Humans Choroid Tomography, Optical Coherence Retinal Diseases Neural Networks, Computer Deep Learning
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DeepCys: Structure-based multiple cysteine function prediction method trained on deep neural network: Case study on domains of unknown functions belonging to COX2 domains.

Proteins Feb 22, 2021
Cysteine (Cys) is the most reactive amino acid participating in a wide range of biological functions. In-silico predictions complement the experiments to meet the need of functional characterization. Multiple Cys function prediction algorithm is scar...
Glutathione Disulfides Sulfonic Acids Software Deep Learning Amino Acid Sequence Electron Transport Complex IV Protein Processing, Post-Translational Sulfides Cysteine Nitroso Compounds Structure-Activity Relationship Cations, Divalent Sulfinic Acids Models, Molecular Protein Structure, Secondary Protein Domains
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