AIMC Topic: Algorithms

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Multicategory individualized treatment regime using outcome weighted learning.

Biometrics
Individualized treatment regimes (ITRs) aim to recommend treatments based on patient-specific characteristics in order to maximize the expected clinical outcome. Outcome weighted learning approaches have been proposed for this optimization problem wi...

Bayesian additive regression trees and the General BART model.

Statistics in medicine
Bayesian additive regression trees (BART) is a flexible prediction model/machine learning approach that has gained widespread popularity in recent years. As BART becomes more mainstream, there is an increased need for a paper that walks readers throu...

Detection of Human Fall Using Floor Vibration and Multi-Features Semi-Supervised SVM.

Sensors (Basel, Switzerland)
Human falls are the premier cause of fatal and nonfatal injuries among older adults. The health outcome of a fall event is largely dependent on rapid response and rescue of the fallen elder. Being able to provide an accurate and fast fall detection w...

Reverse active learning based atrous DenseNet for pathological image classification.

BMC bioinformatics
BACKGROUND: Due to the recent advances in deep learning, this model attracted researchers who have applied it to medical image analysis. However, pathological image analysis based on deep learning networks faces a number of challenges, such as the hi...

Asymptotic Soft Filter Pruning for Deep Convolutional Neural Networks.

IEEE transactions on cybernetics
Deeper and wider convolutional neural networks (CNNs) achieve superior performance but bring expensive computation cost. Accelerating such overparameterized neural network has received increased attention. A typical pruning algorithm is a three-stage...

Transformed ℓ regularization for learning sparse deep neural networks.

Neural networks : the official journal of the International Neural Network Society
Deep Neural Networks (DNNs) have achieved extraordinary success in numerous areas. However, DNNs often carry a large number of weight parameters, leading to the challenge of heavy memory and computation costs. Overfitting is another challenge for DNN...

Age and Sex Estimation Using Artificial Intelligence From Standard 12-Lead ECGs.

Circulation. Arrhythmia and electrophysiology
BACKGROUND: Sex and age have long been known to affect the ECG. Several biologic variables and anatomic factors may contribute to sex and age-related differences on the ECG. We hypothesized that a convolutional neural network (CNN) could be trained t...

Artificial intelligence as an emerging technology in the current care of neurological disorders.

Journal of neurology
BACKGROUND: Artificial intelligence (AI) has influenced all aspects of human life and neurology is no exception to this growing trend. The aim of this paper is to guide medical practitioners on the relevant aspects of artificial intelligence, i.e., m...

Periodicity and finite-time periodic synchronization of discontinuous complex-valued neural networks.

Neural networks : the official journal of the International Neural Network Society
This paper discusses the issue of periodicity and finite-time periodic synchronization of discontinuous complex-valued neural networks (CVNNs). Based on a modified version of Kakutani's fixed point theorem, general conditions are obtained to guarante...

Deeper Profiles and Cascaded Recurrent and Convolutional Neural Networks for state-of-the-art Protein Secondary Structure Prediction.

Scientific reports
Protein Secondary Structure prediction has been a central topic of research in Bioinformatics for decades. In spite of this, even the most sophisticated ab initio SS predictors are not able to reach the theoretical limit of three-state prediction acc...