AIMC Topic: Datasets as Topic

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An Automatic Diagnosis Method of Facial Acne Vulgaris Based on Convolutional Neural Network.

Scientific reports
In this paper, we present a new automatic diagnosis method for facial acne vulgaris which is based on convolutional neural networks (CNNs). To overcome the shortcomings of previous methods which were the inability to classify enough types of acne vul...

Co-occurrence graphs for word sense disambiguation in the biomedical domain.

Artificial intelligence in medicine
Word sense disambiguation is a key step for many natural language processing tasks (e.g. summarization, text classification, relation extraction) and presents a challenge to any system that aims to process documents from the biomedical domain. In thi...

Multilayer bootstrap networks.

Neural networks : the official journal of the International Neural Network Society
Multilayer bootstrap network builds a gradually narrowed multilayer nonlinear network from bottom up for unsupervised nonlinear dimensionality reduction. Each layer of the network is a nonparametric density estimator. It consists of a group of k-cent...

Prediction of influenza-like illness based on the improved artificial tree algorithm and artificial neural network.

Scientific reports
Because influenza is a contagious respiratory illness that seriously threatens public health, accurate real-time prediction of influenza outbreaks may help save lives. In this paper, we use the Twitter data set and the United States Centers for Disea...

Big Data Toolsets to Pharmacometrics: Application of Machine Learning for Time-to-Event Analysis.

Clinical and translational science
Additional value can be potentially created by applying big data tools to address pharmacometric problems. The performances of machine learning (ML) methods and the Cox regression model were evaluated based on simulated time-to-event data synthesized...

Nonnegative Matrix Factorization for identification of unknown number of sources emitting delayed signals.

PloS one
Factor analysis is broadly used as a powerful unsupervised machine learning tool for reconstruction of hidden features in recorded mixtures of signals. In the case of a linear approximation, the mixtures can be decomposed by a variety of model-free B...

Multiclass Classification of Cardiac Arrhythmia Using Improved Feature Selection and SVM Invariants.

Computational and mathematical methods in medicine
Arrhythmia is considered a life-threatening disease causing serious health issues in patients, when left untreated. An early diagnosis of arrhythmias would be helpful in saving lives. This study is conducted to classify patients into one of the sixte...

Microaneurysm detection using fully convolutional neural networks.

Computer methods and programs in biomedicine
BACKROUND AND OBJECTIVES: Diabetic retinopathy is a microvascular complication of diabetes that can lead to sight loss if treated not early enough. Microaneurysms are the earliest clinical signs of diabetic retinopathy. This paper presents an automat...