AIMC Topic: Algorithms

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Percolation in networks with local homeostatic plasticity.

Nature communications
Percolation is a process that impairs network connectedness by deactivating links or nodes. This process features a phase transition that resembles paradigmatic critical transitions in epidemic spreading, biological networks, traffic and transportati...

Mini-batch optimization enables training of ODE models on large-scale datasets.

Nature communications
Quantitative dynamic models are widely used to study cellular signal processing. A critical step in modelling is the estimation of unknown model parameters from experimental data. As model sizes and datasets are steadily growing, established paramete...

Multimodal Imaging of Target Detection Algorithm under Artificial Intelligence in the Diagnosis of Early Breast Cancer.

Journal of healthcare engineering
This study aimed to analyze the diagnostic value of multimodal images based on artificial intelligence target detection algorithms for early breast cancer, so as to provide help for clinical imaging examinations of breast cancer. This article combine...

Metaheuristics with Deep Learning-Enabled Parkinson's Disease Diagnosis and Classification Model.

Journal of healthcare engineering
Parkinson's disease (PD) affects the movement of people, including the differences in writing skill, speech, tremor, and stiffness in muscles. It is significant to detect the PD at the initial stages so that the person can live a peaceful life for a ...

Brain Tumor Detection and Classification by MRI Using Biologically Inspired Orthogonal Wavelet Transform and Deep Learning Techniques.

Journal of healthcare engineering
Radiology is a broad subject that needs more knowledge and understanding of medical science to identify tumors accurately. The need for a tumor detection program, thus, overcomes the lack of qualified radiologists. Using magnetic resonance imaging, b...

Prediction of Lung Infection during Palliative Chemotherapy of Lung Cancer Based on Artificial Neural Network.

Computational and mathematical methods in medicine
Lung infection seriously affects the effect of chemotherapy in patients with lung cancer and increases pain. The study is aimed at establishing the prediction model of infection in patients with lung cancer during chemotherapy by an artificial neural...

Neural Matrix Factorization Recommendation for User Preference Prediction Based on Explicit and Implicit Feedback.

Computational intelligence and neuroscience
Explicit feedback and implicit feedback are two important types of heterogeneous data for constructing a recommendation system. The combination of the two can effectively improve the performance of the recommendation system. However, most of the curr...

Telemetry Data Compression Algorithm Using Balanced Recurrent Neural Network and Deep Learning.

Computational intelligence and neuroscience
Telemetric information is great in size, requiring extra room and transmission time. There is a significant obstruction of storing or sending telemetric information. Lossless data compression (LDC) algorithms have evolved to process telemetric data e...

Using a Selective Ensemble Support Vector Machine to Fuse Multimodal Features for Human Action Recognition.

Computational intelligence and neuroscience
The traditional human action recognition (HAR) method is based on RGB video. Recently, with the introduction of Microsoft Kinect and other consumer class depth cameras, HAR based on RGB-D (RGB-Depth) has drawn increasing attention from scholars and i...

Deep learning applied to breast imaging classification and segmentation with human expert intervention.

Journal of ultrasound
PURPOSE: Automatic classification and segmentation of tumors in breast ultrasound images enables better diagnosis and planning treatment strategies for breast cancer patients.