AIMC Topic: Deep Learning

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AIScaffold: A Web-Based Tool for Scaffold Diversification Using Deep Learning.

Journal of chemical information and modeling
Molecular scaffolds are widely used in drug design. Many methods and tools have been developed to utilize the information in scaffolds. Scaffold diversification is frequently used by medicinal chemists in tasks such as lead compound optimization, but...

Network-based drug sensitivity prediction.

BMC medical genomics
BACKGROUND: Drug sensitivity prediction and drug responsive biomarker selection on high-throughput genomic data is a critical step in drug discovery. Many computational methods have been developed to serve this purpose including several deep neural n...

Deep learning detection of informative features in tau PET for Alzheimer's disease classification.

BMC bioinformatics
BACKGROUND: Alzheimer's disease (AD) is the most common type of dementia, typically characterized by memory loss followed by progressive cognitive decline and functional impairment. Many clinical trials of potential therapies for AD have failed, and ...

Deep learning paired with wearable passive sensing data predicts deterioration in anxiety disorder symptoms across 17-18 years.

Journal of affective disorders
BACKGROUND: Recent studies have demonstrated that passive smartphone and wearable sensor data collected throughout daily life can predict anxiety symptoms cross-sectionally. However, to date, no research has demonstrated the capacity for these digita...

xQSM: quantitative susceptibility mapping with octave convolutional and noise-regularized neural networks.

NMR in biomedicine
Quantitative susceptibility mapping (QSM) provides a valuable MRI contrast mechanism that has demonstrated broad clinical applications. However, the image reconstruction of QSM is challenging due to its ill-posed dipole inversion process. In this stu...

Artificial intelligence and deep learning for small bowel capsule endoscopy.

Digestive endoscopy : official journal of the Japan Gastroenterological Endoscopy Society
Capsule endoscopy is ideally suited to artificial intelligence-based interpretation given its reliance on pattern recognition in still images. Time saving viewing modes and lesion detection features currently available rely on machine learning algori...

Ultrashort echo time time-spatial labeling inversion pulse magnetic resonance angiography with denoising deep learning reconstruction for the assessment of abdominal visceral arteries.

Journal of magnetic resonance imaging : JMRI
Current contrast-enhanced magnetic resonance angiography (MRA) and non-contrast-enhanced balanced steady-state free precession (bSSFP) MRA cause susceptibility artifacts from metallic devices in assessing endovascular visceral-artery interventions. T...

Systems Approach to Pathogenic Mechanism of Type 2 Diabetes and Drug Discovery Design Based on Deep Learning and Drug Design Specifications.

International journal of molecular sciences
In this study, we proposed a systems biology approach to investigate the pathogenic mechanism for identifying significant biomarkers as drug targets and a systematic drug discovery strategy to design a potential multiple-molecule targeting drug for t...

Medical Image Retrieval Using Empirical Mode Decomposition with Deep Convolutional Neural Network.

BioMed research international
Content-based medical image retrieval (CBMIR) systems attempt to search medical image database to narrow the semantic gap in medical image analysis. The efficacy of high-level medical information representation using features is a major challenge in ...