AIMC Topic: Neural Networks, Computer

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Comparison of wavelet transformations to enhance convolutional neural network performance in brain tumor segmentation.

BMC medical informatics and decision making
INTRODUCTION AND GOAL TO BACKGROUND: Due to the importance of segmentation of MRI images in identifying brain tumors, various methods including deep learning have been introduced for automatic brain tumor segmentation. On the other hand, using a comb...

A tree based approach for multi-class classification of surgical procedures using structured and unstructured data.

BMC medical informatics and decision making
BACKGROUND: In surgical department, CPT code assignment has been a complicated manual human effort, that entails significant related knowledge and experience. While there are several studies using CPTs to make predictions in surgical services, litera...

Spliceator: multi-species splice site prediction using convolutional neural networks.

BMC bioinformatics
BACKGROUND: Ab initio prediction of splice sites is an essential step in eukaryotic genome annotation. Recent predictors have exploited Deep Learning algorithms and reliable gene structures from model organisms. However, Deep Learning methods for non...

Machine Learning-Based Gynecologic Tumor Diagnosis and Its Postoperative Incisional Infection Influence Factor Analysis.

Journal of healthcare engineering
Various factors influencing postoperative incisional infection in gynecologic tumors were analyzed, and the value of quality nursing intervention was studied. In this study, 74 surgically treated gynecologic tumor patients were randomly selected from...

Construction of Financial Management Early Warning Model Based on Improved Ant Colony Neural Network.

Computational intelligence and neuroscience
With the advent of the era of economic globalization, the world capital market is also facing financial risks. It is necessary to have a corresponding financial management early warning model to reduce economic losses. This paper uses the combination...

Scene Text Recognition Based on Bidirectional LSTM and Deep Neural Network.

Computational intelligence and neuroscience
Deep learning is a subfield of artificial intelligence that allows the computer to adopt and learn some new rules. Deep learning algorithms can identify images, objects, observations, texts, and other structures. In recent years, scene text recogniti...

Machine learning and deep learning enabled fuel sooting tendency prediction from molecular structure.

Journal of molecular graphics & modelling
Soot formation models become increasingly important in advanced renewable fuels formulation for soot reduction benefit. This work evaluates performance of machine learning (ML) and deep learning (DL) to predict yield sooting index (YSI) from chemical...

A deep learning framework with an embedded-based feature selection approach for the early detection of the Alzheimer's disease.

Computers in biology and medicine
Ageing is associated with various ailments including Alzheimer 's disease (AD), which is a progressive form of dementia. AD symptoms develop over a period of years and, unfortunately, there is no cure. Existing AD treatments can only slow down the pr...

An adversarial discriminative temporal convolutional network for EEG-based cross-domain emotion recognition.

Computers in biology and medicine
Domain adaptation (DA) tackles the problem where data from the source domain and target domain have different underlying distributions. In cross-domain (cross-subject or cross-dataset) emotion recognition based on EEG signals, traditional classificat...

Deep learning approaches for de novo drug design: An overview.

Current opinion in structural biology
De novo drug design is the process of generating novel lead compounds with desirable pharmacological and physiochemical properties. The application of deep learning (DL) in de novo drug design has become a hot topic, and many DL-based approaches have...