AIMC Topic: Neural Networks, Computer

Clear Filters Showing 21471 to 21480 of 31376 articles

Individualized prediction of depressive disorder in the elderly: A multitask deep learning approach.

International journal of medical informatics
INTRODUCTION: Depressive disorder is one of the major public health problems among the elderly. An effective depression risk prediction model can provide insights on the disease progression and potentially inform timely targeted interventions. Theref...

Deep-learning model for predicting 30-day postoperative mortality.

British journal of anaesthesia
BACKGROUND: Postoperative mortality occurs in 1-2% of patients undergoing major inpatient surgery. The currently available prediction tools using summaries of intraoperative data are limited by their inability to reflect shifting risk associated with...

Neural network-based approaches for biomedical relation classification: A review.

Journal of biomedical informatics
The explosive growth of biomedical literature has created a rich source of knowledge, such as that on protein-protein interactions (PPIs) and drug-drug interactions (DDIs), locked in unstructured free text. Biomedical relation classification aims to ...

Adversarial training based lattice LSTM for Chinese clinical named entity recognition.

Journal of biomedical informatics
Clinical named entity recognition (CNER), which intends to automatically detect clinical entities in electronic health record (EHR), is a committed step for further clinical text mining. Recently, more and more deep learning models are used to Chines...

Single patient convolutional neural networks for real-time MR reconstruction: a proof of concept application in lung tumor segmentation for adaptive radiotherapy.

Physics in medicine and biology
Investigate 3D (spatial and temporal) convolutional neural networks (CNNs) for real-time on-the-fly magnetic resonance imaging (MRI) reconstruction. In particular, we investigated the applicability of training CNNs on a patient-by-patient basis for t...

Correlation-Based Ensemble Feature Selection Using Bioinspired Algorithms and Classification Using Backpropagation Neural Network.

Computational and mathematical methods in medicine
A framework for clinical diagnosis which uses bioinspired algorithms for feature selection and gradient descendant backpropagation neural network for classification has been designed and implemented. The clinical data are subjected to data preprocess...

System-Pharmacology Dissection of Traditional Chinese herbs SINI Decoction for Treatment of Cardiovascular Diseases.

Anais da Academia Brasileira de Ciencias
Abstract: Cardiovascular diseases (CVDs) are leading causes of death in the world, owing to noticeable incidence and mortality. Traditional Chinese Medicine (TCM) SINI Decoction (SND) is used to prevent and treat CVDs, which has attracted extensive ...

Finite-time resilient H state estimation for discrete-time delayed neural networks under dynamic event-triggered mechanism.

Neural networks : the official journal of the International Neural Network Society
In this paper, the finite-time resilient H state estimation problem is investigated for a class of discrete-time delayed neural networks. For the sake of energy saving, a dynamic event-triggered mechanism is employed in the design of state estimator ...

A survey of adaptive resonance theory neural network models for engineering applications.

Neural networks : the official journal of the International Neural Network Society
This survey samples from the ever-growing family of adaptive resonance theory (ART) neural network models used to perform the three primary machine learning modalities, namely, unsupervised, supervised and reinforcement learning. It comprises a repre...

Salience-aware adaptive resonance theory for large-scale sparse data clustering.

Neural networks : the official journal of the International Neural Network Society
Sparse data is known to pose challenges to cluster analysis, as the similarity between data tends to be ill-posed in the high-dimensional Hilbert space. Solutions in the literature typically extend either k-means or spectral clustering with additiona...