AIMC Topic: Databases, Factual

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Inter-foetus Membrane Segmentation for TTTS Using Adversarial Networks.

Annals of biomedical engineering
Twin-to-Twin Transfusion Syndrome is commonly treated with minimally invasive laser surgery in fetoscopy. The inter-foetal membrane is used as a reference to find abnormal anastomoses. Membrane identification is a challenging task due to small field ...

Dilated Skip Convolution for Facial Landmark Detection.

Sensors (Basel, Switzerland)
Facial landmark detection has gained enormous interest for face-related applications due to its success in facial analysis tasks such as facial recognition, cartoon generation, face tracking and facial expression analysis. Many studies have been prop...

The use of natural language processing to identify vaccine-related anaphylaxis at five health care systems in the Vaccine Safety Datalink.

Pharmacoepidemiology and drug safety
PURPOSE: The objective was to develop a natural language processing (NLP) algorithm to identify vaccine-related anaphylaxis from plain-text clinical notes, and to implement the algorithm at five health care systems in the Vaccine Safety Datalink.

A Hierarchical Recurrent Neural Network for Symbolic Melody Generation.

IEEE transactions on cybernetics
In recent years, neural networks have been used to generate symbolic melodies. However, the long-term structure in the melody has posed great difficulty to design a good model. In this article, we present a hierarchical recurrent neural network (HRNN...

Discriminative margin-sensitive autoencoder for collective multi-view disease analysis.

Neural networks : the official journal of the International Neural Network Society
Medical prediction is always collectively determined based on bioimages collected from different sources or various clinical characterizations described from multiple physiological features. Notably, learning intrinsic structures from multiple hetero...

Analysis of Decision Tree and K-Nearest Neighbor Algorithm in the Classification of Breast Cancer.

Asian Pacific journal of cancer prevention : APJCP
OBJECTIVE: The death rate of breast tumour is falling as there is progress in its research area. However, it is the most common disease among women. It is a great challenge in designing a machine learning model to evaluate the performance of the clas...

Neonatal seizure detection from raw multi-channel EEG using a fully convolutional architecture.

Neural networks : the official journal of the International Neural Network Society
A deep learning classifier for detecting seizures in neonates is proposed. This architecture is designed to detect seizure events from raw electroencephalogram (EEG) signals as opposed to the state-of-the-art hand engineered feature-based representat...

Who is the Winner? Memristive-CMOS Hybrid Modules: CNN-LSTM Versus HTM.

IEEE transactions on biomedical circuits and systems
Hierarchical, modular and sparse information processing are signature characteristics of biological neural networks. These aspects have been the backbone of several artificial neural network designs of the brain-like networks, including Hierarchical ...

Fully-automated deep learning-powered system for DCE-MRI analysis of brain tumors.

Artificial intelligence in medicine
Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) plays an important role in diagnosis and grading of brain tumors. Although manual DCE biomarker extraction algorithms boost the diagnostic yield of DCE-MRI by providing quantitative infor...

Brain age prediction using deep learning uncovers associated sequence variants.

Nature communications
Machine learning algorithms can be trained to estimate age from brain structural MRI. The difference between an individual's predicted and chronological age, predicted age difference (PAD), is a phenotype of relevance to aging and brain disease. Here...