AIMC Topic: Algorithms

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A novel graph convolutional neural network for predicting interaction sites on protein kinase inhibitors in phosphorylation.

Scientific reports
Protein kinase-inhibitor interactions are key to the phosphorylation of proteins involved in cell proliferation, differentiation, and apoptosis, which shows the importance of binding mechanism research and kinase inhibitor design. In this study, a no...

Research on Chest Disease Recognition Based on Deep Hierarchical Learning Algorithm.

Journal of healthcare engineering
Chest X-ray has become one of the most common ways in diagnostic radiology exams, and this technology assists expert radiologists with finding the patients at potential risk of cardiopathy and lung diseases. However, it is still a challenge for exper...

Research on Teaching Resource Recommendation Algorithm Based on Deep Learning and Cognitive Diagnosis.

Journal of healthcare engineering
With the increasing abundance of network teaching resources, the recommendation technology based on network is becoming more and more mature. There are differences in the effect of recommendation, which leads to great differences in the effect of rec...

Deep-Learning-Based Cancer Profiles Classification Using Gene Expression Data Profile.

Journal of healthcare engineering
The quantity of data required to give a valid analysis grows exponentially as machine learning dimensionality increases. In a single experiment, microarrays or gene expression profiling assesses and determines gene expression levels and patterns in v...

Computed Tomography Image Features under Deep Learning Algorithm Applied in Staging Diagnosis of Bladder Cancer and Detection on Ceramide Glycosylation.

Computational and mathematical methods in medicine
The research is aimed at investigating computed tomography (CT) image based on deep learning algorithm and the application value of ceramide glycosylation in diagnosing bladder cancer. The images of ordinary CT detection were improved. In this study,...

Edge Caching in Fog-Based Sensor Networks through Deep Learning-Associated Quantum Computing Framework.

Computational intelligence and neuroscience
Fog computing (FC) based sensor networks have emerged as a propitious archetype for next-generation wireless communication technology with caching, communication, and storage capacity services in the edge. Mobile edge computing (MEC) is a new era of ...

E-Commerce Credit Risk Assessment Based on Fuzzy Neural Network.

Computational intelligence and neuroscience
In this paper, we propose a cooperative strategy-based self-organization mechanism to reconstruct the network. The mechanism includes a comprehensive evaluation algorithm and structure adjustment mechanism. The self-organization mechanism can be carr...

Increasing neural network robustness improves match to macaque V1 eigenspectrum, spatial frequency preference and predictivity.

PLoS computational biology
Task-optimized convolutional neural networks (CNNs) show striking similarities to the ventral visual stream. However, human-imperceptible image perturbations can cause a CNN to make incorrect predictions. Here we provide insight into this brittleness...

Clinical acceptance of deep learning reconstruction for abdominal CT imaging: objective and subjective image quality and low-contrast detectability assessment.

European radiology
OBJECTIVE: To evaluate the image quality and clinical acceptance of a deep learning reconstruction (DLR) algorithm compared to traditional iterative reconstruction (IR) algorithms.

Coal identification based on a deep network and reflectance spectroscopy.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
The rapid identification of coal types in the field is an important task. This research combines spectroscopy with deep learning algorithms and proposes a method for quickly identifying coal types in the field. First, we collect field spectral data o...