AIMC Topic: Deep Learning

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DeepPLM_mCNN: An approach for enhancing ion channel and ion transporter recognition by multi-window CNN based on features from pre-trained language models.

Computational biology and chemistry
Accurate classification of membrane proteins like ion channels and transporters is critical for elucidating cellular processes and drug development. We present DeepPLM_mCNN, a novel framework combining Pretrained Language Models (PLMs) and multi-wind...

Financial impact of incorporating deep learning reconstruction into magnetic resonance imaging routine.

European journal of radiology
PURPOSE: Artificial intelligence and deep learning solutions are increasingly utilized in healthcare and radiology. The number of studies addressing their enhancement of productivity and monetary impact is, however, still limited. Our hospital has fa...

Deep learning-based target decomposition for markerless lung tumor tracking in radiotherapy.

Medical physics
BACKGROUND: In radiotherapy, real-time tumor tracking can verify tumor position during beam delivery, guide the radiation beam to target the tumor, and reduce the chance of a geometric miss. Markerless kV x-ray image-based tumor tracking is challengi...

Deep Learning-Based construction of a Drug-Like compound database and its application in virtual screening of HsDHODH inhibitors.

Methods (San Diego, Calif.)
The process of virtual screening relies heavily on the databases, but it is disadvantageous to conduct virtual screening based on commercial databases with patent-protected compounds, high compound toxicity and side effects. Therefore, this paper uti...

Unpaired deep learning for pharmacokinetic parameter estimation from dynamic contrast-enhanced MRI without AIF measurements.

NeuroImage
DCE-MRI provides information about vascular permeability and tissue perfusion through the acquisition of pharmacokinetic parameters. However, traditional methods for estimating these pharmacokinetic parameters involve fitting tracer kinetic models, w...

eDeeplepsy: An artificial neural framework to reveal different brain states in children with epileptic spasms.

Epilepsy & behavior : E&B
OBJECTIVE: Despite advances, analysis and interpretation of EEG still essentially rely on visual inspection by a super-specialized physician. Considering the vast amount of data that composes the EEG, much of the detail inevitably escapes ordinary hu...

Integration of lanthanide MOFs/methylcellulose-based fluorescent sensor arrays and deep learning for fish freshness monitoring.

International journal of biological macromolecules
Preserving fish meat poses a significant challenge due to its high protein and low fat content. This study introduces a novel approach that utilizes a common type of lanthanide metal-organic frameworks (Ln-MOFs), EuMOFs, in combination with 5-fluores...

Application of deep learning in predicting suspended sediment concentration: A case study in Jiaozhou Bay, China.

Marine pollution bulletin
Previous research methodologies for quantifying Suspended Sediment Concentration (SSC) have encompassed in-situ observations, numerical simulations, and analyses of remote sensing datasets, each with inherent constraints. In this study, we have harne...

Deep-learning automated quantification of longitudinal OCT scans demonstrates reduced RPE loss rate, preservation of intact macular area and predictive value of isolated photoreceptor degeneration in geographic atrophy patients receiving C3 inhibition treatment.

The British journal of ophthalmology
OBJECTIVE: To evaluate the role of automated optical coherence tomography (OCT) segmentation, using a validated deep-learning model, for assessing the effect of C3 inhibition on the area of geographic atrophy (GA); the constituent features of GA on O...

Distribution and determinants of choroidal vascularity index in healthy eyes from deep-learning choroidal analysis: a population-based SS-OCT study.

The British journal of ophthalmology
AIMS: To quantify the profiles of choroidal vascularity index (CVI) using fully artificial intelligence (AI)-based algorithm applied to swept-source optical coherence tomography (SS-OCT) images and evaluate the determinants of CVI in a population-bas...