AIMC Topic: Deep Learning

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Applying deep learning to defect detection in printed circuit boards via a newest model of you-only-look-once.

Mathematical biosciences and engineering : MBE
In this paper, a new model known as YOLO-v5 is initiated to detect defects in PCB. In the past many models and different approaches have been implemented in the quality inspection for detection of defect in PCBs. This algorithm is specifically select...

Rib fracture detection in computed tomography images using deep convolutional neural networks.

Medicine
To evaluate the rib fracture detection performance in computed tomography (CT) images using a software based on a deep convolutional neural network (DCNN) and compare it with the rib fracture diagnostic performance of doctors.We included CT images fr...

Interpretation of deep learning in genomics and epigenomics.

Briefings in bioinformatics
Machine learning methods have been widely applied to big data analysis in genomics and epigenomics research. Although accuracy and efficiency are common goals in many modeling tasks, model interpretability is especially important to these studies tow...

DeepTorrent: a deep learning-based approach for predicting DNA N4-methylcytosine sites.

Briefings in bioinformatics
DNA N4-methylcytosine (4mC) is an important epigenetic modification that plays a vital role in regulating DNA replication and expression. However, it is challenging to detect 4mC sites through experimental methods, which are time-consuming and costly...

DeepVF: a deep learning-based hybrid framework for identifying virulence factors using the stacking strategy.

Briefings in bioinformatics
Virulence factors (VFs) enable pathogens to infect their hosts. A wealth of individual, disease-focused studies has identified a wide variety of VFs, and the growing mass of bacterial genome sequence data provides an opportunity for computational met...

Deep4mC: systematic assessment and computational prediction for DNA N4-methylcytosine sites by deep learning.

Briefings in bioinformatics
DNA N4-methylcytosine (4mC) modification represents a novel epigenetic regulation. It involves in various cellular processes, including DNA replication, cell cycle and gene expression, among others. In addition to experimental identification of 4mC s...

MLCDForest: multi-label classification with deep forest in disease prediction for long non-coding RNAs.

Briefings in bioinformatics
The long non-coding RNAs (lncRNAs) are subject of intensive recent studies due to its association with various human diseases. It is desirable to build the artificial intelligence-based models for prediction of diseases or tissues based on the lncRNA...

Different molecular enumeration influences in deep learning: an example using aqueous solubility.

Briefings in bioinformatics
Aqueous solubility is the key property driving many chemical and biological phenomena and impacts experimental and computational attempts to assess those phenomena. Accurate prediction of solubility is essential and challenging, even with modern comp...

A novel deep learning method for predictive modeling of microbiome data.

Briefings in bioinformatics
With the development and decreasing cost of next-generation sequencing technologies, the study of the human microbiome has become a rapid expanding research field, which provides an unprecedented opportunity in various clinical applications such as d...

Closed-loop feedback control of microfluidic cell manipulation deep-learning integrated sensor networks.

Lab on a chip
Microfluidic technologies have long enabled the manipulation of flow-driven cells en masse under a variety of force fields with the goal of characterizing them or discriminating the pathogenic ones. On the other hand, a microfluidic platform is typic...