AIMC Topic: Deep Learning

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[Prediction of gene mutation in lung cancer based on deep learning and histomorphology analysis].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi
Lung cancer is a most common malignant tumor of the lung and is the cancer with the highest morbidity and mortality worldwide. For patients with advanced non-small cell lung cancer who have undergone epidermal growth factor receptor (EGFR) gene mutat...

Deep-learning with synthetic data enables automated picking of cryo-EM particle images of biological macromolecules.

Bioinformatics (Oxford, England)
MOTIVATION: Single-particle cryo-electron microscopy (cryo-EM) has become a powerful technique for determining 3D structures of biological macromolecules at near-atomic resolution. However, this approach requires picking huge numbers of macromolecula...

DeepCleave: a deep learning predictor for caspase and matrix metalloprotease substrates and cleavage sites.

Bioinformatics (Oxford, England)
MOTIVATION: Proteases are enzymes that cleave target substrate proteins by catalyzing the hydrolysis of peptide bonds between specific amino acids. While the functional proteolysis regulated by proteases plays a central role in the 'life and death' c...

DeepMSPeptide: peptide detectability prediction using deep learning.

Bioinformatics (Oxford, England)
SUMMARY: The protein detection and quantification using high-throughput proteomic technologies is still challenging due to the stochastic nature of the peptide selection in the mass spectrometer, the difficulties in the statistical analysis of the re...

Analysis of several key factors influencing deep learning-based inter-residue contact prediction.

Bioinformatics (Oxford, England)
MOTIVATION: Deep learning has become the dominant technology for protein contact prediction. However, the factors that affect the performance of deep learning in contact prediction have not been systematically investigated.

Convolutional neural network-based approach to estimate bulk optical properties in diffuse optical tomography.

Applied optics
Deep learning has been actively investigated for various applications such as image classification, computer vision, and regression tasks, and it has shown state-of-the-art performance. In diffuse optical tomography (DOT), the accurate estimation of ...

Deep learning predicts function of live retinal pigment epithelium from quantitative microscopy.

The Journal of clinical investigation
Increases in the number of cell therapies in the preclinical and clinical phases have prompted the need for reliable and noninvasive assays to validate transplant function in clinical biomanufacturing. We developed a robust characterization methodolo...

A deep neural network based hierarchical multi-label classification method.

The Review of scientific instruments
With the accumulation of data generated by biological experimental instruments, using hierarchical multi-label classification (HMC) methods to process these data for gene function prediction has become very important. As the structure of the widely u...

The diagnostic accuracy of artificial intelligence in thoracic diseases: A protocol for systematic review and meta-analysis.

Medicine
INTRODUCTION: Thoracic diseases include a variety of common human primary malignant tumors, among which lung cancer and esophageal cancer are among the top 10 in cancer incidence and mortality. Early diagnosis is an important part of cancer treatment...