AIMC Topic: Algorithms

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Prediction of Hematoma Expansion in Intracerebral Hemorrhage in 24 Hours by Machine Learning Algorithm.

World neurosurgery
OBJECTIVE: The significance of noncontrast computer tomography (CT) image markers in predicting hematoma expansion (HE) following intracerebral hemorrhage (ICH) within different time intervals in the initial 24 hours after onset may be uncertain. Hen...

MonteCat: A Basin-Hopping-Inspired Catalyst Descriptor Search Algorithm for Machine Learning Models.

Journal of chemical information and modeling
Proposing relevant catalyst descriptors that can relate the information on a catalyst's composition to its actual performance is an ongoing area in catalyst informatics, as it is a necessary step to improve our understanding on the target reactions. ...

Fully-automated multi-organ segmentation tool applicable to both non-contrast and post-contrast abdominal CT: deep learning algorithm developed using dual-energy CT images.

Scientific reports
A novel 3D nnU-Net-based of algorithm was developed for fully-automated multi-organ segmentation in abdominal CT, applicable to both non-contrast and post-contrast images. The algorithm was trained using dual-energy CT (DECT)-obtained portal venous p...

A Novel Data Augmentation Approach Using Mask Encoding for Deep Learning-Based Asynchronous SSVEP-BCI.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Deep learning (DL)-based methods have been successfully employed as asynchronous classification algorithms in the steady-state visual evoked potential (SSVEP)-based brain-computer interface (BCI) system. However, these methods often suffer from the l...

Exploring Prognostic Gene Factors in Breast Cancer via Machine Learning.

Biochemical genetics
Breast cancer remains the most prevalent cancer in women. To date, its underlying molecular mechanisms have not been fully uncovered. The determination of gene factors is important to improve our understanding on breast cancer, which can correlate th...

SecureNet: Proactive intellectual property protection and model security defense for DNNs based on backdoor learning.

Neural networks : the official journal of the International Neural Network Society
With the widespread application of deep neural networks (DNNs), the risk of privacy breaches against DNN models is constantly on the rise, resulting in an increasing need for intellectual property (IP) protection for such models. Although neural netw...

Robust noise-aware algorithm for randomized neural network and its convergence properties.

Neural networks : the official journal of the International Neural Network Society
The concept of randomized neural networks (RNNs), such as the random vector functional link network (RVFL) and extreme learning machine (ELM), is a widely accepted and efficient network method for constructing single-hidden layer feedforward networks...

A Review of Machine Learning Algorithms for Biomedical Applications.

Annals of biomedical engineering
As the amount and complexity of biomedical data continue to increase, machine learning methods are becoming a popular tool in creating prediction models for the underlying biomedical processes. Although all machine learning methods aim to fit models ...

Acceleration of Graph Neural Network-Based Prediction Models in Chemistry via Co-Design Optimization on Intelligence Processing Units.

Journal of chemical information and modeling
Atomic structure prediction and associated property calculations are the bedrock of chemical physics. Since high-fidelity ab initio modeling techniques for computing the structure and properties can be prohibitively expensive, this motivates the deve...