AIMC Topic: Neural Networks, Computer

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Myo-regressor Deep Informed Neural NetwOrk (Myo-DINO) for fast MR parameters mapping in neuromuscular disorders.

Computer methods and programs in biomedicine
Magnetic Resonance (MR) parameters mapping in muscle Magnetic Resonance Imaging (mMRI) is predominantly performed using pattern recognition-based algorithms, which are characterised by high computational costs and scalability issues in the context of...

Schizophrenia diagnosis using the GRU-layer's alpha-EEG rhythm's dependability.

Psychiatry research. Neuroimaging
Verifying schizophrenia (SZ) can be assisted by deep learning techniques and patterns in brain activity observed in alpha-EEG recordings. The suggested research provides evidence of the reliability of alpha-EEG rhythm in a Gated-Recurrent-Unit-based ...

Unsupervised adversarial neural network for enhancing vasculature in photoacoustic tomography images using optical coherence tomography angiography.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Photoacoustic tomography (PAT) is a powerful imaging modality for visualizing tissue physiology and exogenous contrast agents. However, PAT faces challenges in visualizing deep-seated vascular structures due to light scattering, absorption, and reduc...

Multitask Learning on Graph Convolutional Residual Neural Networks for Screening of Multitarget Anticancer Compounds.

Journal of chemical information and modeling
Recently, various modern experimental screening pipelines and assays have been developed to find promising anticancer drug candidates. However, it is time-consuming and almost infeasible to screen an immense number of compounds for anticancer activit...

Integrating graph convolutional networks to enhance prompt learning for biomedical relation extraction.

Journal of biomedical informatics
BACKGROUND AND OBJECTIVE: Biomedical relation extraction aims to reveal the relation between entities in medical texts. Currently, the relation extraction models that have attracted much attention are mainly to fine-tune the pre-trained language mode...

Optimized deep CNN for detection and classification of diabetic retinopathy and diabetic macular edema.

BMC medical imaging
Diabetic Retinopathy (DR) and Diabetic Macular Edema (DME) are vision related complications prominently found in diabetic patients. The early identification of DR/DME grades facilitates the devising of an appropriate treatment plan, which ultimately ...

Prediction of treatment outcome for branch retinal vein occlusion using convolutional neural network-based retinal fluorescein angiography.

Scientific reports
Deep learning techniques were used in ophthalmology to develop artificial intelligence (AI) models for predicting the short-term effectiveness of anti-VEGF therapy in patients with macular edema secondary to branch retinal vein occlusion (BRVO-ME). 1...

Convolutional neural network-based regression analysis to predict subnuclear chromatin organization from two-dimensional optical scattering signals.

Journal of biomedical optics
SIGNIFICANCE: Azimuth-resolved optical scattering signals obtained from cell nuclei are sensitive to changes in their internal refractive index profile. These two-dimensional signals can therefore offer significant insights into chromatin organizatio...

A neural network approach to predict opioid misuse among previously hospitalized patients using electronic health records.

PloS one
Can Electronic Health Records (EHR) predict opioid misuse in general patient populations? This research trained three backpropagation neural networks to explore EHR predictors using existing patient data. Model 1 used patient diagnosis codes and was ...

Comparison of machine learning methods for genomic prediction of selected Arabidopsis thaliana traits.

PloS one
We present a comparison of machine learning methods for the prediction of four quantitative traits in Arabidopsis thaliana. High prediction accuracies were achieved on individuals grown under standardized laboratory conditions from the 1001 Arabidops...