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Gene Expression Classification of Lung Adenocarcinoma into Molecular Subtypes.

IEEE/ACM transactions on computational biology and bioinformatics
As one of the most common malignancies in the world, lung adenocarcinoma (LUAD) is currently difficult to cure. However, the advent of precision medicine provides an opportunity to improve the treatment of lung cancer. Subtyping lung cancer plays an ...

Visual Exploration of Neural Document Embedding in Information Retrieval: Semantics and Feature Selection.

IEEE transactions on visualization and computer graphics
Neural embeddings are widely used in language modeling and feature generation with superior computational power. Particularly, neural document embedding - converting texts of variable-length to semantic vector representations - has shown to benefit w...

Predicting protein-peptide interaction sites using distant protein complexes as structural templates.

Scientific reports
Protein-peptide interactions play an important role in major cellular processes, and are associated with several human diseases. To understand and potentially regulate these cellular function and diseases it is important to know the molecular details...

Unsupervised classification of multi-omics data during cardiac remodeling using deep learning.

Methods (San Diego, Calif.)
Integration of multi-omics in cardiovascular diseases (CVDs) presents high potentials for translational discoveries. By analyzing abundance levels of heterogeneous molecules over time, we may uncover biological interactions and networks that were pre...

Study on Hesitant Fuzzy Information Measures and Their Clustering Application.

Computational intelligence and neuroscience
At present, research on hesitant fuzzy operations and measures is based on equal length processing, and an equal length processing method will inevitably destroy the original data structure and change the data information. This is an urgent problem t...

Retinal blood vessel extraction employing effective image features and combination of supervised and unsupervised machine learning methods.

Artificial intelligence in medicine
In medicine, retinal vessel analysis of fundus images is a prominent task for the screening and diagnosis of various ophthalmological and cardiovascular diseases. In this research, a method is proposed for extracting the retinal blood vessels employi...

Model-based hearing diagnostics based on wideband tympanometry measurements utilizing fuzzy arithmetic.

Hearing research
Today's audiometric methods for the diagnosis of middle ear disease are often based on a comparison of measurements with standard curves, that represent the statistical range of normal hearing responses. Because of large inter-individual variances in...

Simultaneous spatiotemporal tracking and oxygen sensing of transient implants in vivo using hot-spot MRI and machine learning.

Proceedings of the National Academy of Sciences of the United States of America
A varying oxygen environment is known to affect cellular function in disease as well as activity of various therapeutics. For transient structures, whether they are unconstrained therapeutic transplants, migrating cells during tumor metastasis, or ce...

Unsupervised Learning Approach for Comparing Multiple Transposon Insertion Sequencing Studies.

mSphere
Transposon insertion sequencing (TIS) is a widely used technique for conducting genome-scale forward genetic screens in bacteria. However, few methods enable comparison of TIS data across multiple replicates of a screen or across independent screens,...