AIMC Topic: Algorithms

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DeepIDC: A Prediction Framework of Injectable Drug Combination Based on Heterogeneous Information and Deep Learning.

Clinical pharmacokinetics
BACKGROUND AND OBJECTIVE: In clinical practice, injectable drug combination (IDC) usually provides good therapeutic effects for patients. Numerous clinical studies have directly indicated that inappropriate IDC generates adverse drug events (ADEs). T...

Research on a Bearing Fault Enhancement Diagnosis Method with Convolutional Neural Network Based on Adaptive Stochastic Resonance.

Sensors (Basel, Switzerland)
As a powerful feature extraction tool, a convolutional neural network (CNN) has strong adaptability for big data applications such as bearing fault diagnosis, whereas the classification performance is limited when the quality of raw signals is poor. ...

A novel genetic-artificial neural network based age estimation system.

Scientific reports
Age estimation is the ability to predict the age of an individual based on facial clues. This could be put to practical use in underage voting detection, underage driving detection, and overage sportsmen detection. To date, no popular automatic age e...

Novel deep learning hybrid models (CNN-GRU and DLDL-RF) for the susceptibility classification of dust sources in the Middle East: a global source.

Scientific reports
Dust storms have many negative consequences, and affect all kinds of ecosystems, as well as climate and weather conditions. Therefore, classification of dust storm sources into different susceptibility categories can help us mitigate its negative eff...

A parallel integrated learning technique of improved particle swarm optimization and BP neural network and its application.

Scientific reports
Swarm intelligence algorithm has attracted a lot of interest since its development, which has been proven to be effective in many application areas. In this study, an enhanced integrated learning technique of improved particle swarm optimization and ...

The Health Gym: synthetic health-related datasets for the development of reinforcement learning algorithms.

Scientific data
In recent years, the machine learning research community has benefited tremendously from the availability of openly accessible benchmark datasets. Clinical data are usually not openly available due to their confidential nature. This has hampered the ...

Deep reinforcement learning and its applications in medical imaging and radiation therapy: a survey.

Physics in medicine and biology
Reinforcement learning takes sequential decision-making approaches by learning the policy through trial and error based on interaction with the environment. Combining deep learning and reinforcement learning can empower the agent to learn the interac...

DeepProjection: specific and robust projection of curved 2D tissue sheets from 3D microscopy using deep learning.

Development (Cambridge, England)
The efficient extraction of image data from curved tissue sheets embedded in volumetric imaging data remains a serious and unsolved problem in quantitative studies of embryogenesis. Here, we present DeepProjection (DP), a trainable projection algorit...

A novel hybrid transformer-CNN architecture for environmental microorganism classification.

PloS one
The success of vision transformers (ViTs) has given rise to their application in classification tasks of small environmental microorganism (EM) datasets. However, due to the lack of multi-scale feature maps and local feature extraction capabilities, ...

Seq2Morph: A deep learning deformable image registration algorithm for longitudinal imaging studies and adaptive radiotherapy.

Medical physics
PURPOSE: To simultaneously register all the longitudinal images acquired in a radiotherapy course for analyzing patients' anatomy changes for adaptive radiotherapy (ART).