AIMC Topic: Deep Learning

Clear Filters Showing 14471 to 14480 of 28423 articles

Classifying tumor brain images using parallel deep learning algorithms.

Computers in biology and medicine
One of the most important resources used in today's world is image. Medical images can play an essential role in helping diagnose diseases. Doctors and specialists use medical images to diagnose brain diseases. Convolution neural networks are among t...

SiBERT: A Siamese-based BERT network for Chinese medical entities alignment.

Methods (San Diego, Calif.)
Entity alignment aims at associating semantically similar entities in knowledge graphs from different sources. It is widely used in the integration and construction of professional medical knowledge. The existing deep learning methods lack term-level...

DR-only Carbon-ion radiotherapy treatment planning via deep learning.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
PURPOSE: To evaluate the feasibility of patient-specific digital radiography (DR)-only treatment planning for carbon ion radiotherapy in anthropomorphic thorax-and-abdomen phantom and head-and-neck patients.

Classification of multi-differentiated liver cancer pathological images based on deep learning attention mechanism.

BMC medical informatics and decision making
PURPOSE: Liver cancer is one of the most common malignant tumors in the world, ranking fifth in malignant tumors. The degree of differentiation can reflect the degree of malignancy. The degree of malignancy of liver cancer can be divided into three t...

Intelligent Fault Diagnosis for Chemical Processes Using Deep Learning Multimodel Fusion.

IEEE transactions on cybernetics
Deep learning technology has been widely used in fault diagnosis for chemical processes. However, most deep learning technologies currently adopted only use a single network stack or a certain network stack with multilayer perceptron (MLP) behind it....

Deep learning-based microarray cancer classification and ensemble gene selection approach.

IET systems biology
Malignancies and diseases of various genetic origins can be diagnosed and classified with microarray data. There are many obstacles to overcome due to the large size of the gene and the small number of samples in the microarray. A combination strateg...

A Modified Deep Learning Framework for Arrhythmia Disease Analysis in Medical Imaging Using Electrocardiogram Signal.

BioMed research international
Arrhythmias are anomalies in the heartbeat rhythm that occur occasionally in people's lives. These arrhythmias can lead to potentially deadly consequences, putting your life in jeopardy. As a result, arrhythmia identification and classification are a...

Optimization Model of Mathematics Instructional Mode Based on Deep Learning Algorithm.

Computational intelligence and neuroscience
This paper proposes corresponding teaching methods and instructional modes based on predecessors' research on mathematics instructional mode and the current state of mathematics teaching. In addition, this paper constructs a teaching evaluation model...

PCA-Based Incremental Extreme Learning Machine (PCA-IELM) for COVID-19 Patient Diagnosis Using Chest X-Ray Images.

Computational intelligence and neuroscience
Novel coronavirus 2019 has created a pandemic and was first reported in December 2019. It has had very adverse consequences on people's daily life, healthcare, and the world's economy as well. According to the World Health Organization's most recent ...

EEGSym: Overcoming Inter-Subject Variability in Motor Imagery Based BCIs With Deep Learning.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
In this study, we present a new Deep Learning (DL) architecture for Motor Imagery (MI) based Brain Computer Interfaces (BCIs) called EEGSym. Our implementation aims to improve previous state-of-the-art performances on MI classification by overcoming ...