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Multi-Label Classification With Dual Tail-Node Augmentation for Drug Repositioning.

IEEE/ACM transactions on computational biology and bioinformatics
Due to the lengthy and costly process of new drug discovery, increasing attention has been paid to drug repositioning, i.e., identifying new drug-disease associations. Current machine learning methods for drug repositioning mainly leverage matrix fac...

Artificial Intelligence Models for Cell Type and Subtype Identification Based on Single-Cell RNA Sequencing Data in Vision Science.

IEEE/ACM transactions on computational biology and bioinformatics
Single-cell RNA sequencing (scRNA-seq) provides a high throughput, quantitative and unbiased framework for scientists in many research fields to identify and characterize cell types within heterogeneous cell populations from various tissues. However,...

Deep learning and clustering approaches for dental implant size classification based on periapical radiographs.

Scientific reports
This study investigated two artificial intelligenceĀ (AI) methods for automatically classifying dental implant diameter and length based on periapical radiographs. The first method, deep learning (DL), involved utilizing the pre-trained VGG16 model an...

Swarm Smart Meta-Estimator for 2D/2D Heterostructure Design.

Journal of chemical information and modeling
Two-dimensional (2D) semiconductors are central to many scientific fields. The combination of two semiconductors (heterostructure) is a good way to lift many technological deadlocks. Although ab initio calculations are useful to study physical proper...

Identifying cancer risks using spectral subset feature selection based on multi-layer perception neural network for premature treatment.

Computer methods in biomechanics and biomedical engineering
Recently, human beings have been affected mainly by dreadful cancer diseases. Predicting cancer risk levels is a major challenge in biomedical research for feature selection and classification at the margins. To resolve this problem, we propose a Sub...

A topological classifier to characterize brain states: When shape matters more than variance.

PloS one
Despite the remarkable accuracies attained by machine learning classifiers to separate complex datasets in a supervised fashion, most of their operation falls short to provide an informed intuition about the structure of data, and, what is more impor...

A self-training algorithm based on the two-stage data editing method with mass-based dissimilarity.

Neural networks : the official journal of the International Neural Network Society
A self-training algorithm is a classical semi-supervised learning algorithm that uses a small number of labeled samples and a large number of unlabeled samples to train a classifier. However, the existing self-training algorithms consider only the ge...

Embedding-based terminology expansion via secondary use of large clinical real-world datasets.

Journal of biomedical informatics
A log-likelihood based co-occurrence analysis of ∼1.9 million de-identified ICD-10 codes and related short textual problem list entries generated possible term candidates at a significance level of p<0.01. These top 10 term candidates, consisting of ...

A Fuzzy Clustering Approach to Identify Pedestrians' Traffic Behavior Patterns.

Journal of research in health sciences
BACKGROUND: Pattern recognition of pedestrians' traffic behavior can enhance the management efficiency of interested groups by targeting access to them and facilitating planning via more specific surveys. This study aimed to evaluate the pedestrians'...

Pumping machine fault diagnosis based on fused RDC-RBF.

PloS one
At present, the fault diagnosis of pumping units in major oil fields in China is time-consuming and inefficient, and there is no universal problem for high requirements of hardware resources. In this study, a fault fusion diagnosis method of pumping ...