AI Medical Compendium Topic:
Cluster Analysis

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A machine learning approach to predict healthcare cost of breast cancer patients.

Scientific reports
This paper presents a novel machine learning approach to perform an early prediction of the healthcare cost of breast cancer patients. The learning phase of our prediction method considers the following two steps: (1) in the first step, the patients ...

coupleCoC+: An information-theoretic co-clustering-based transfer learning framework for the integrative analysis of single-cell genomic data.

PLoS computational biology
Technological advances have enabled us to profile multiple molecular layers at unprecedented single-cell resolution and the available datasets from multiple samples or domains are growing. These datasets, including scRNA-seq data, scATAC-seq data and...

A supervised clustering MCMC methodology for large categorical feature spaces.

Statistical methods in medical research
There is a well-established tradition within the statistics literature that explores different techniques for reducing the dimensionality of large feature spaces. The problem is central to machine learning and it has been largely explored under the u...

Search for H-Bonded Motifs in Liquid Ethylene Glycol Using a Machine Learning Strategy.

The journal of physical chemistry. B
Trajectories of atomic positions derived from molecular dynamics (AIMD) simulations of H-bonded liquids contain a wealth of information on dominant structural motifs and recurrent patterns of association. Extracting this information from a detailed ...

Spectral embedding network for attributed graph clustering.

Neural networks : the official journal of the International Neural Network Society
Attributed graph clustering aims to discover node groups by utilizing both graph structure and node features. Recent studies mostly adopt graph neural networks to learn node embeddings, then apply traditional clustering methods to obtain clusters. Ho...

Unsupervised multi-sense language models for natural language processing tasks.

Neural networks : the official journal of the International Neural Network Society
Existing language models (LMs) represent each word with only a single representation, which is unsuitable for processing words with multiple meanings. This issue has often been compounded by the lack of availability of large-scale data annotated with...

A joint deep learning model enables simultaneous batch effect correction, denoising, and clustering in single-cell transcriptomics.

Genome research
Recent developments of single-cell RNA-seq (scRNA-seq) technologies have led to enormous biological discoveries. As the scale of scRNA-seq studies increases, a major challenge in analysis is batch effects, which are inevitable in studies involving hu...

Machine Learning in Cardiac Imaging: Exploring the Art of Cluster Analysis.

Journal of the American Society of Echocardiography : official publication of the American Society of Echocardiography

Non-Contact Respiration Measurement Method Based on RGB Camera Using 1D Convolutional Neural Networks.

Sensors (Basel, Switzerland)
Conventional respiration measurement requires a separate device and/or can cause discomfort, so it is difficult to perform routinely, even for patients with respiratory diseases. The development of contactless respiration measurement technology would...